Thesis_3_10

i

AACCKKNNOOWWLLEEDDGGEEMMEENNTTSS

I would first like to thank God for making this all possible. I also owe a debt of

gratitude to DDrr.. AAhhmmeedd RRaagghheebb, for his encouragement and help with this project.

Another debt of gratitude is also due to DDrr.. KKhhaalleedd SShhaawwkkii, who was patient,

helping and encouraging throughout the writing. I must also thank DDrr.. WWaaeell KKaammeell

and DDrr.. HHeesshhaamm BBaassssiioouunnyy for their instructions.

Finally, without the love and support of my parents, and the rest of my family, I

could not have survived the first semester of graduate school, much less conducted

this research.

ii

AABBSSTTRRAACCTT

Earthmoving operations are often among the most vital operations in many

construction projects owing to their significant effect on the project cost and

duration. A trade-off between the highest production rate and the lowest cost of

earthmoving operations is most desirable. Therefore, it would be advantageous to

develop a tool to assist the managers of such projects in the decision making

process. A Decision Support Tool (PROEQUIP) utilizing simulation has been

developed in this research to assist in the selection of the appropriate earthmoving

combination of the hauling and excavating units. PROEQUIP can also predict and

help in monitoring the production rate and cost of earthmoving operations. Unlike

most previous methods and techniques which have been devised to simulate either

production rate or cost, PROEQUIP can simultaneously simulate the production rate

and cost of earthmoving operation using any available combination of equipment,

hauled material and road characteristics. PROEQUIP comprises an expandable

database and two calculation modules. The database contains the empty weight,

maximum payload, loaded truck speed, horsepower and heaped capacity for 27

types of trucks. Weight and filling factor characteristics of 23 materials as well as

the rolling resistance of 21 road materials are also stored in the database. The two

modules included into PROEQUIP can retrieve any data needed from this database.

The first of these two is a deterministic performance module which uses

commonplace empirical relationships to calculate the cost and production rate for a

specific combination of road and excavation material, and truck and excavator

specifications. The second module uses the simulation technique to predict the cost

and production rate for a number of possible combinations of truck/excavator

systems. PROEQUIP was validated using data collected from an earthmoving

project in Egypt and another in Saudi Arabia. The actual production rates were

estimated at the lower 7th and 28th percentile of the results simulated by

PROEQUIP, respectively.

iii

TTAABBLLEE OOFF CCOONNTTEENNTTSS

ACKNOWLEDGEMENTS ............................................................................. i

ABSTRACT………………………………………………………………….ii

LIST OF FIGURES ........................................................................................ v

LIST OF TABLES ......................................................................................... ix

LIST OF SYMBOLS ...................................................................................... xi

CHAPTER 1: GENERAL INTRODUCTION ............................................. 1

1.1 INTRODUCTION ........................................................................................ 2

1.2 RESEARCH AIM AND OBJECTIVES ...................................................... 3

1.3 ORGANIZATION OF THE RESEARCH ................................................... 4

1.4RESEARCHSCOPE AND LIMITATIONS ................................................. 5

1.5LAYOUT ANDMETHODOLOGY OF PROEQUIP ................................... 6

CHAPTER 2: REVIEW OF LITERATURE ............................................... 8

2.1 INTRODUCTION ........................................................................................ 9

2.2 GENERAL REVIEW ................................................................................... 9

2.3COMPUTERS IN EARTHMOVING ......................................................... 12

CHAPTER 3: EARTHMOVING OPERATIONS ..................................... 21

3.1 INTRODUCTION ...................................................................................... 22

3.2 MANAGING EARTHMOVING OPERATIONS ..................................... 22

3.2.1 Safety ................................................................................................... 23

3.3HYDRAULIC EXCAVATORS .................................................................. 26

3.4 TRUCKS AND HAULING OPERATIONS ............................................. 30

CHAPTER 4: ESTIMATING TECHNIQUES .......................................... 34

4.1 INTRODUCTION ...................................................................................... 35

4.2 PRODUCTIVITY ESTIMATING ............................................................. 36

4.3 COST ESTIMATING ................................................................................ 50

4.3.1 Fixed Costs .......................................................................................... 52

4.3.2 Operating Costs ................................................................................... 54

4.3.3 Labor Costs .......................................................................................... 58

4.4 SELECTING THE OPTIMUM EQUATION TO CALCULATE

TRUCK SPEED ........................................................................................ 58

iv

CHAPTER 5: DECISION SUPPORT TOOL FOR EARTHMOVING

PROJECTS ......................................................................... 61

5.1 INTRODUCTION ...................................................................................... 62

5.2 INPUTS, OUTPUTS AND DATABASE .................................................. 63

5.3 SYSTEM STRUCTURE ............................................................................ 69

5.3.1 System Calculation .............................................................................. 69

5.3.2 The Simulation .................................................................................... 74

5.4 USER INTERFACE ................................................................................... 79

5.5 THE RESULTS .......................................................................................... 85

5.6 EXAMPLES FOR TRADITIONAL CALCULATION USING

PROEQUIP (PROEQUIP VERIFICATION) ........................................... 92

5.6.1 Example 1 ............................................................................................ 92

5.6.2 Example 2 ............................................................................................ 99

5.7 THE SIMULATION RESULTS ACCURACY: ...................................... 104

5.8 APPLICATION OF PROEQUIP ON REAL CASES: ............................ 105

CHAPTER 6: CONCLUSION AND RECOMMENDATIONS ............. 125

6.1 SUMMARY AND CONCLUSION ......................................................... 126

6.2 RECOMMENDATIONS FOR FUTURE RESEARCHE ........................ 128

REFERENCES.. .......................................................................................... 130

APPENDICES.. ........................................................................................... 135

Appendix A..................................................................................................... 136

Appendix B ..................................................................................................... 146

Appendix C ..................................................................................................... 149

Appendix D..................................................................................................... 151

Appendix E ..................................................................................................... 154

Appendix F ..................................................................................................... 156

v

LLIISSTT OOFF FFIIGGUURREESS

List of Figures Page

Figure 1.1 PROEQUIP results summary ……………………………… 7

Figure 2.1 A Graphical Model for Maximizing Production of a Pushed

Scraper ……………………………………………………... 10

Figure 3.1 Hydraulic hoe loading a truck ……………………………... 28

Figure 3.2 Wheel-mounted hydraulic hoe …………………………….. 28

Figure 3.3 Basic parts of a hydraulic hoe ……………………………... 28

Figure 3.4 Hydraulic hoe bucket capacity rating dimensions ………… 28

Figure 3.5 Maximize production of the earthmoving system ………… 29

Figure 3.6 Truck tractor unit towing ………………………………….. 31

Figure 3.7 Off-highway truck …………………………………………. 31

Figure 3.8 Highway rigid-frame rear-dump truck …………………….. 32

Figure 3.9 An articulated dump truck …………………………………. 32

Figure 3.10 An articulated dump truck moving through soft ground ….. 32

Figure 3.11 Off-highway tractor towing a loaded bottom-dump trailer .. 32

Figure 3.12 Highway bottom-dump ……………………………………. 32

Figure 3.13 Measurement of volumetric capacity …………………….... 33

Figure 4.1 Material-Volume Changes Caused by Construction

Processes …………………………………………………... 36

Figure 4.2 Performance chart for Caterpillar 793C Truck ……………. 47

Figure 4.3 Basic truck load cycle ……………………………………… 48

Figure 4.4 Equipment Cost Model …………………………………….. 51

Figure 5.1 Soil properties database figure …………………………… 65

Figure 5.2 Road condition database figure ………………………….. 66

Figure 5.3 Trucks form to add, edit and delete truck …………………. 67

Figure 5.4 Trucks form to search for existing truck …………………... 67

Figure 5.5 User interface parameters flowchart ………………………. 68

Figure 5.6 Production calculation flowchart for earthmoving system .. 70

vi

LLIISSTT OOFF FFIIGGUURREESS ((CCoonntt’’dd))


Figure 5.7 Unit cost calculation flowchart for earthmoving system …...... 71

Figure 5.8 Simulation model network diagram for the activities ……….. 77

Figure 5.9 Normal probability distribution for the random variables ….. 77

Figure 5.10 Beta probability distribution for the random variables ……… 77

Figure 5.11 The simulation model pseudocode …………………………... 78

Figure 5.12 User interface – Project information ………………………… 79

Figure 5.13 User interface – Job information ……………………………... 80

Figure 5.15 User interface – Haul road information ……………………… 81

Figure 5.15 User interface – Equipment selection section ……………….. 82

Figure 5.16 User interface – Equipment Unit Cost section ………………. 83

Figure 5.17 User interface – Equipment Cost section ……………………. 83

Figure 5.18 User interface – Simulation section ………………………….. 84

Figure 5.19 The production and cost results page ………………………… 85

Figure 5.20 The results data sheet page …………………………………... 86

Figure 5.21 The simulation calculations interface – trials section A …….. 88

Figure 5.22 The simulation calculations interface – trials section B …….. 88

Figure 5.23 The simulation calculations interface – trials section C …….. 88

Figure 5.24 The simulation results – unit cost ……………………………. 89

Figure 5.25 The simulation results – Production …………………………. 89

Figure 5.26 The overlay charts for productivity and cost ……………….... 90

Figure 5.27 The recommendations (advices) page ……………………….. 91

Figure 5.28 Safety video sample in the recommendations ……………….. 91

Figure 5.29 Caterpillar 725 Articulated Truck specifications ……………. 93

Figure 5.30 The results of example 1 in the Results page ………………… 98

Figure 5.31 Caterpillar 725 Articulated Truck specifications ……………. 99

vii



Figure 5.32 The results of example 2 in the Results page ………………… 103

Figure 5.33 GAZADCO project (site plan) ……………………………….. 106

Figure 5.34 GAZADCO project (shrimp pond works) …………………… 107

Figure 5.35 GAZADCO project (Earthmoving works) …………………… 107

Figure 5.36 GAZADCO project (Excavation works A) …………………... 108

Figure 5.37 GAZADCO project (excavation works B) …………………… 108

Figure 5.38 GAZADCO project (excavation works C) …………………… 109

Figure 5.39 GAZADCO project - Mercedes Benz 3328K (1987) ………... 111

Figure 5.40 GAZADCO project - Mercedes Benz 2638 (1993) ………….. 111


Figure 5.42 GAZADCO project - Volvo – FM12.420 (2004) ……………. 111

Figure 5.43 GAZADCO project - Mercedes Benz 2628(1983) ………….. 111

Figure 5.44 GAZADCO project - Hyundai R140 LC – 7 ………………… 111

Figure 5.45 GAZADCO project - Caterpillar 325 DL ……………………. 112



Figure 5.48 GAZADCO project - Kumatsu PC240 LC …………………... 112

Figure 5.49 GAZADCO project - Caterpillar 225 ………………………... 112

Figure 5.50 The productivity distribution for the first case ………………. 113

Figure 5.51 The simulation overlay charts for all study cases ……………. 114

Figure 5.52 The suggesting optimum cases to be selected …………….…. 115

Figure 5.53 NILE COMPANY project (site works) ……………………… 118

Figure 5.54 NILE COMPANY project - Mercedes Benz 3331 …………... 119

Figure 5.55 NILE COMPANY project - Scania 113H …………………… 119

Figure 5.56 Kumatsu PW160 ……………………………………………... 119

viii



Figure 5.57 Kumatsu PC210 LC …………………………………………. 119

Figure 5.58 The productivity distribution for the first case ……………. 120

Figure 5.59 The simulation overlay charts for all study cases …………… 121

Figure 5.60 The suggesting optimum cases to be selected ….……….…. 122

Figure 5.61 The simulation overlay - probability - charts for all study

cases …………………………………………………………. 124

Figure 6.1 The organization of the research ……………………………. 126

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LLIISSTT OOFF TTAABBLLEESS

List of Tables Page

Table 2.1 PROEQUIP and previous published models for earthmoving 18

Table 4.1 Material Volume Conversion Factors ………………………... 37

Table 4.2 Loading excavator cycle times for a 90o swing (seconds) …... 39

Table 4.3 Excavator swing factors ……………………………………… 41

Table 4.4 Weight of Materials according to German Norm DIN/VOB ... 41

Table 4.5 Typical rolling resistance factors …………………………….. 44

Table 4.6 Operator Skill Factor, FO........................................................... 45

Table 4.7 Job Efficiency Factor, Fe……………………………………... 45

Table 4.8 Excavator operating efficiency ……………………………… 45

Table 4.9 Selecting ownership period based on operating conditions… 53

Table 4.10 Maintenance and repair rates as a percentage of the hourly

depreciation for selected equipment ………………………… 55

Table 4.11 Weights, fuel consumption rates, and load factors for diesel

and gasoline engines …………………………………………. 56

Table 4.12 Guidelines for tire life for off-highway equipment ………….. 57

Table 4.13 Summary of example 1 …...………………………………… 59

Table 4.14 Summary of example 2 …….……………………………….. 60

Table 5.1 Parameters for the Random Variables Used in the Models … 76

Table 5.2 User Interface – Window 1 description …………………….. 79

Table 5.3 User Interface – Window 2 description ……………………. 80

Table 5.4 User Interface – Window 3 description ……………………. 81

Table 5.5 User Interface – Window 4 description ……………………... 82

Table 5.6 User Interface – Windows5 and 6description ……………... 84

Table 5.7 User Interface – Window 7 description …………………….. 84

Table 5.8 The results of example 1 using PROEQUIP software ……… 98

Table 5.9 The results of example 2 using PROEQUIP software ……… 103

Table 5.10 The production results according to number of trials change 104

x

LLIISSTT OOFF TTAABBLLEESS ((CCoonntt’’dd))

List of Tables Page

Table 5.11 GAZADCO Project data and description ………..………….. 105

Table 5.12 GAZADCO Project Company Equipment (Trucks) ………... 109

Table 5.13 GAZADCO Project Company Equipment (Excavators) ……. 110

Table 5.14 GAZADCO Project Equipment available for renting

(Trucks) ……………………………………………………... 110

Table 5.15 GAZADCO Project Equipment available for renting

(Excavators) …………………………………………………. 110

Table 5.16 Kabary-Matrooh Project data and description ……………… 117

Table 5.17 Kabary-Matrooh Project Company Equipment (Trucks) ....... 118

Table 5.18 Kabary-Matrooh Project Equipment for renting (Excavators) 119

xi

LLIISSTT OOFF SSYYMMBBOOLLSS

SYMBOLS NOMENCLATURES UNIT

Average material density ton/m3

A Equipment Availability factor

AS:D Angle of swing and depth (height) of cut

correction

B Bucket capacity m3

Bc Nominal bucket capacity m3

BCM Bank Cubic Meter m3

Bf Bucket fill factor

C Theoretical cycles/hr for a 90o swing cycles/hr

c2, c3 Rolling resistance constant

Cbe Bucket heaped capacity m3

CCM Compacted Cubic Meter m3

CECE The Committee on European Construction

Equipment

Cht Truck heaped capacity m3

CIPROS knowledge based construction planning

simulation system

cr Rolling coefficient

CYCLONE Cyclic Operations Network

Di Distance from haul to dump site km

D Equipment depreciation per hour LE/hr

Dd Number of working days per week day

Dh Number of working hours per day hour

DISCO Graphical simulation modeling for bridge

construction

E Equipment efficiency

xii

LLIISSTT OOFF SSYYMMBBOOLLSS ((CCoonntt’’dd))


e Engine efficiency

ESEMPS Expert system using for road equipment

F Fuel cost per hour LE/hr

ff Bucket fill factor

Fl Fuel cost per liter LE

Ft Tractive force N

GHP The gross engine horsepower at governed engine

rpm

hp

GMW Gross machine weight kg

GR Road Grade resistance N

GPSS General Purpose Simulation System

h Helper cost per hour LE/hr

hp Equipment engine horse power hp

hpt Truck engine net power hp

HSM The Hierarchical Simulation Model

I Interest cost per hour LE/hr

i Interest rate %

IS Insurance cost per hour LE/hr

is Insurance rate %

K The weight of fuel used per brake hp/hour kg/br.hp-hr

KPL The weight of fuel kg/liter

L Labor cost per hour LE/hr

LCM Loose Cubic Meter m3

LF The load factor

LMPH The liters used per machine hour liter

xiii



Lt Rated truck load ton

M Maintenance and repair cost per hour LE/hr

m Vehicle mass kg

MicroCYCLONE Cyclic Operations Network using

microcomputers

Mta Mass on tractive Rear axle kg

Nb Number of excavator buckets bucket

Nh Number of helpers Helper

Nt Number of trucks truck

O Job operational factor

OA Equipment Operating Efficiency

Pe Energy power kW

P Production m3/hr

PCSA Power Crane and Shovel Association

Pt Truck payload kg

PTF Propel time factor kg

Q heaped bucket capacity m3

Qs Excavator productivity m3/hr

Qt Truck productivity m3/hr

Rr Road Rolling resistance N

Rt Road Total resistance N

S Salvage value LE

s Slope of haul road %

Sf Swing factor

SAE Society of Automotive Engineers

SIMPHONY Special purpose construction simulation model

xiv



SPS Special Purpose Simulation

STROBOSCOPE State and Resource-Based Simulation of

Construction Processes

te Excavator cycle time Sec

T Taxes cost per hour LE/hour

t Taxes rate %

tc Excavator cycle time for a 90o swing min.

TC Total unit cost per hour LE/hour

Tcc Tire change (replacement) cost LE

tce Excavator cycle time sec.

Tct Total truck cycle time min.

tct Truck cycle time min.

td Dump time min.

th Haul time min.

Tic Tire cost per hour LE/hour

tL Load time min.

tr Approximate tire life hours

tr Return time min.

TR Total resistance N

U Lubricant cost per hour LE/hour

UM-CYCLONE Cyclic Operations Network under DOS system

V Truck speed km/hr

VC volume correction for loose volume to bank

volume

VH Velocity of haul direction km/hr

Vhe Truck speed empty km/hr

Vhl Truck speed loaded km/hr

xv



Vl Load volume m3

Wet Truck empty weight kg

Wf Weight fully loaded ton

Wgt Gross weight of the truck kg

Wl Load weight kg

Ws Weight of soil kg/ m3

η Transmission efficiency

μ Coefficient of friction

CCHHAAPPTTEERR OONNEE

GGEENNEERRAALL IINNTTRROODDUUCCTTIIOONN

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CCHHAAPPTTEERR 11

GGEENNEERRAALL IINNTTRROODDUUCCTTIIOONN

11..11 IINNTTRROODDUUCCTTIIOONN

Construction is an important industry in terms of the annual capital invested in

construction work and its high employment. The importance of the industry can also

be measured by its contribution to the gross national product. However, the

construction industry is in a difficult position due to the decline in construction

productivity which started in the mid 1970's [1]. The current stringent financial

situation aggravates these difficulties.

Facing these challenging problems, the construction industry became aware of the

importance of productivity improvement and cost reduction, and is striving for such

improvements. Historically, productivity improvement was often focused on labor

effort; this also applied to the construction industry. But there is a second important

term in production improvement especially in construction industry which is the

earthmoving equipment [1].

Earthmoving may include site preparation, excavation, embankment construction,

backfilling, dredging, preparing base course, subbase, subgrade, compaction, and

road surfacing. The types of equipment used and the environmental conditions will

affect the man- machine-hours required to complete a given amount of work. Before

preparing estimates, there is a need to select the best method of operation and the

type of equipment to use. Each piece of equipment is specifically designed to

perform certain mechanical tasks. Therefore, the equipment selection should be

based on efficient operation and availability. Earthmoving is characterized by the

intensive utilization of machines. It is therefore often one of the most important

operations in many construction projects in terms of its cost and productivity.

3

Hence, earthmoving planning is a potential area for further productivity

improvement.

To improve earthmoving planning, a variety of methods and techniques has been

tried. The rapid development of computer technology provides a useful means to

assist in construction management and planning. Proper equipment selection is

crucial to achieve efficient earthmoving and construction operations. The machine‘s

operational capabilities and equipment availability should be considered when

selecting this machine for a particular task. The manager should visualize how best

to employ the available equipment based on soil considerations, zone of operation,

and project-specific requirements. Cost and productivity estimates, productivity

control, and production records are the basis for management decisions. Therefore,

it is helpful to have a common method of recording, directing, and reporting

production.

11..22 RREESSEEAARRCCHH AAIIMM AANNDD OOBBJJEECCTTIIVVEESS

This research addresses the development of a decision supporting tool which could

be used for the selection of appropriate earthmoving equipment and for the

estimation of their productivity and cost. Furthermore, provide some important

safety recommendations for using earthmoving operations are later provided.

The overall aim of this research is to develop a simulation model in the form of

computer application to assist managers to manage and estimate the productivity,

duration and cost of earthmoving system.

In order to attain the above aim, four specific objectives will have to be achieved:

1) Collection of data needed to compile required databases of:

Equipment database: provide truck empty weight, truck payload, truck

horsepower, top loaded speed of the truck and truck heaped capacity

Excavated material database: provide material weight, bucket fill

factor and excavator cycle time based on material type.

4

Rolling resistance database based on haul road type.

2) Design a mathematical model to perform the calculations necessary to

estimate productivity rate, cost and duration for a given earthmoving system

to be used for monitoring, control and improvement of ongoing operations.

3) Obtain performance data for as many earthmoving systems as possible to be

used in the simulation.

4) Design a simulation model integrated with a mathematical model to enable

the comparison among presented earthmoving systems.

11..33 OORRGGAANNIIZZAATTIIOONN OOFF TTHHEE RREESSEEAARRCCHH

The remainder of this research is organized as follows:

Chapter 2 covers a literature survey. The goal of this chapter is to present a

comprehensive review of the previous efforts on improving earthmoving project

performance, especially earthmoving equipment planning and selection using a

mathematical model or simulation.

Chapter 3 presents general information about two major earthmoving equipments:

trucks and excavators. This information can help in the selection of appropriate

equipment for particular earthmoving operations under certain working conditions.

Earthmoving equipment productivity and cost are the major parameters in the

selection of appropriate machines for earthmoving operations.

Chapter 4 discusses the productivity and cost estimating of earthmoving equipment

and factors influencing productivity.

Chapter 5addressesthe decision support tool (PROEQUIP) and explains the

component of this application and its database. The application user interface data

and the source of those data are presented.

Finally, Conclusions and Recommendations for further research development are

presented in Chapter 6.

5

Appendices include a list of selected visual basic programming codes, excavator

cycle time estimating method, unit cost calculation form and Excel formulas which

have been used in the simulation model.

11..44 RREESSEEAARRCCHHSSCCOOPPEE AANNDD LLIIMMIITTAATTIIOONNSS

Earthmoving equipment planning and management deals with a wide range of

issues, including equipment financing, standardization, maintenance scheduling,

replacement schemes, safety and routine operational planning. The focus of this

research is on:

1. The operational planning, particularly on the development of a computer

decision support tool which could be used for the selection of appropriate

earthmoving equipment to complete a given job

2. The estimation of the cost and duration of the job

In earthmoving operations, earthworks may include loosening, excavating, loading,

hauling, unloading, placing, spreading, grading, and compacting. For simplicity of

the tool, this research deals only with four phases: excavating, loading, hauling and

unloading.

The main outcome of this research is an interactive advisory decision support tool

for equipment selection which facilitates the comparison among the performances

of different earthmoving systems working under specified jobsite conditions

according to the following points:

1) The parameters that may affect equipment performance are described in

Chapter 3. However, the measurement of these parameters in the field was

not conducted.

2) It is assumed that the operator will always operate the truck at a constant

speed regardless of any acceleration and deceleration. In reality, however,

the operator will not operate the machine at maximum performance

6

throughout the haul segment and it might be possible that the operator never

operates the machine at maximum performance in a certain segment.

3) Earthmoving system production and unit cost is calculated using the

estimation technique described in detail in Chapter 4.

4) Not all equipment categories will be modeled (equipment categories describe

their general function, or type) and not all classes within each category will

be modeled (classes describe the weight, horsepower, or size of equipment

within its category);the categories and classes that will be analyzed are

machines that are fairly common throughout the industry. The study will be

limited to Caterpillar Articulated trucks, Caterpillar excavators and

equipment that will be described in the "Cases of Study" section in chapter 5.

5) Travel time will be calculated using the equation based on equipment

performance charts contained in the Caterpillar Performance Handbook [1]

that will be validated by two examples in chapter 4.

6) This work is also limited in that it will analyze historical data from a

relatively small number of companies. This does not necessarily mean that

the simulation result represent every firm type, size, geographic region, or

management style. Every construction company is unique. The study is

limited to the medium size construction industry projects that will be

described in the "Cases of Study" section in chapter 5. Mining and huge

projects were not being investigated.

7) The tool that will be developed in this research can be used by the contractor,

planners, project managers and construction engineers. The study

assumptions will be presented in "The Simulation" section in the chapter 5.

11..55 LLAAYYOOUUTT AANNDDMMEETTHHOODDOOLLOOGGYY OOFF PPRROOEEQQUUIIPP

A computer application (PROEQUIP) was developed using Microsoft Visual

Basic.Net and consists of three interfaces:

7

1. User Interface: is the one which the user will use to input the required

parameters.

2. Calculations and results interface: deals with calculations involved in

estimating production and the final results of production, duration and cost

and simulation results. The simulation part of this interface will be developed

using CRYSTAL BALL as an Excel add-in integrated within PROEQUIP,

Figure 1.1.

3. Recommendations Interface: is the location of some important safety

recommendations to assist applying safety while using earthmoving system.

Figure 1.1 PROEQUIP results summary

SIMULATION MODEL

•what is the best system to work in this area?

•What is the economical equipment combination to finish the required job?

•Which site part will be finished first?

•What is the best system to finish the job faster?

PERFORMANCE ASSESSMENT AND OPTIMIZATION RESULTS

•Does the existing equipment combination work fine?

•How to manage this job to gain the maximum productivity?

•What are number of trucks and buckets required to minimize the system cost?

•What are number of trucks and buckets required to provide maximum productivity?

•When does this equipment combination finish the required job?

•Does this equipment combination can progress the work on time?

•Does this equipment combination work as required or the work is behind the schedule?

Database

CCHHAAPPTTEERR TTWWOO

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9

CCHHAAPPTTEERR 22

RREEVVIIEEWW OOFF LLIITTEERRAATTUURREE


The literature review in this chapter contains two parts. The first part is an overview

of the research development in the area of earthmoving and the methods and

techniques used in previous work. The second part presents several models closely

associated with earthmoving equipment and deals with computer-aided programs

used in earthmoving projects.

22..22 GGEENNEERRAALL RREEVVIIEEWW

As the earthmoving planning process is a comprehensive one driven by many

factors, the identification of these factors is particularly important. Studies have

been conducted on these factors and their treatment. To find the solutions to specific

problems in earthmoving, many methods and techniques have been tried.

The Caterpillar Tractor Company developed a graphical model in 1968 (see Figure

2.1) for solving the machine matching problem by analyzing machine output. In

developing this model, it was found that the load of a scraper increases rapidly, but

the loading rate decreases as the scraper capacity is approached as shown by line

BDO in Figure 2.1 [1].

In Figure 2.1, the vertical axis indicates the amount of material loaded, and the

horizontal axis represents certain parts of the cycle time. Line BDO is a typical

load-growth curve for a bottom-loading scraper pushed by a track type tractor. Line

AO (2.7 minutes) is the cycle time les the loading time for this particular scraper

and soil, line CO (0.3 minutes) is the cycle time less the loading time of the pusher.

The slopes of lines connected from points A and C to the load-growth curve BDO

indicate the output per unit time of the scraper and loader respectively, and the two

10

lines would have their steepest slopes (maximum output per unit time) if they were

drawn tangential to the load-growth curve. In each case, the optimum loads are

determined to be about 31 and 23 cubic meters with pushing time being 0.8 and

0.35 minutes respectively. If the pusher works with two or more scrapers, this

model can determine the most optimum production of the fleet when the costs of the

pusher and scrapers are considered [1].

Figure 2.1 A Graphical Model for Maximizing Production of a Pushed

Scraper

In 1968, Griffis issued a paper on Queuing Theory and optimizing haul fleet size.

The main components of Queuing system are interiors (customers) and service

suppliers. When a customer refers to a system for receiving service, two different

cases may happen. If one of the service suppliers is free, then giving the service to

the customer begins immediately. On the other hand if all service suppliers are

busy, then the customers should wait and thus the queue will be made. In the truck

filling and refilling problem, the trucks are assumed as the customers of Queuing

system. Loaders are known as service providers in this system. One loader along

with specified number of trucks is known as a Queuing system. The objective of

solving this problem is to determine the number of loaders and trucks in a manner to

11

increase the probability of truck existence for one loader as much as possible. In

other words, by allocating appropriate number of trucks the loader will be always

busy [2].

In earthmoving operations, it is common for different types of machines to work

together to complete a job task. For instance, a Loader-truck fleet is often used to

move earth. Gates and Scarpa pointed out that a trade-off should be made between a

lesser number of large and expensive hauling units and a greater number of small

and relatively inexpensive hauling units [3]. Later, Gates and Scarpa carried out

research into the factors that affect the selection of earthmoving equipment and

summarized these factors into four categories [4]:

1) Spatial Relationships: In this category, the major factors were identified to be

the elevation of the working platform, the face and level of excavation,

obstructions in excavation and the configuration of excavation.

2) Soi1 Characteristics: This category covers the soil's ability to support

excavators and hauling units and other soi1 characteristics such as traction,

rolling resistance and gradeability.

3) Contract Provisions: The factors in this category include the quantities of

excavation, moving, and fill; the allowable time of construction; provisions

for payment cash flow.

4) Logistical Considerations: The factors included in this category involve the

availability of equipment and operators with applicable experience; the time

and cost to mobilize and demobilize crews; the use of equipment in

preceding and in subsequent operations (resource leveling); rental costs,

ownership costs, operating costs and production rates.

In 1989, Karshenas developed a model by applying probability theory to determine

the capacity and number of trucks matching the given loaders in a fleet. The

solutions of the model were given in several graphical formats. According to the

loader capacities, the capacity-number combinations of trucks, which possess a

minimum cost of production, can be quickly determined [5].

12

Heavy vehicles have high influence on pavement structure at the roads. Karami has

and Gillespie in 1993 paid attention on pavement damage from trucks and how to

predict dynamic loads along the roadways also the validity of the models is

presented. The authors focused on characteristics of trucks and pavement, and also

their interaction [6] [7].

In 1995, York and Maze briefly described applications of trucks size and weights

standards in the US. This research contains evaluation of truck size and weight

regulation in the United States and classification of performance criteria [8].

And in 2001 Nagatani has studied into the problem of modeling bunching

transitions in general traffic flow and bus routes. Bunching models capture the

tendency of moving objects to bunch together when moving in a line. This is

usually due to some of the objects being operated or moving more efficiently than

others. It can also be due to small unpredictable delays. Bunching is known to

reduce a fleet‘s ability to meet its maximum capacity [9].

22..33 CCOOMMPPUUTTEERRSS IINN EEAARRTTHHMMOOVVIINNGG

Several attempts have been made to develop computer-aided tools to assist in

equipment selection. For example, applications of simulation techniques to

earthmoving operations were made in the 1960s [10]. In 1972, Willenbrock

developed a model using a computer simulation language, GPSS (General Purpose

Simulation System), to estimate cost for earthworks. The GPSS is a programming

system designed for the simulation of discrete systems. These are systems that can

be modeled as a series of state changes that occur instantaneously, usually over a

period of time. Complexities in their analysis arise because there are many elements

in the system, and there is competition for limited system resources. The simulation

technique uses numerical computation methods to follow the system elements

through their changes of state, and predicts properties of the system from

measurements on the model. GPSS came into existence rapidly, with virtually no

planning, and surprisingly little effort. It came rapidly because it filled an urgent

13

need that left little time for exploring alternatives. The lack of planning came from a

happy coincidence of a solution meeting its problem at the right time. The economy

of effort was based on a background of experience in the type of application for

which the language was designed, both on the part of the designer and the early

users [10].

Simulation has been used extensively in many areas of Construction Engineering

starting with the introduction of CYCLONE by Halpin in 1977. This methodology

has been the basis for a number of construction simulation systems. Most of these

systems are general in nature forcing users to build models using abstract elements

such as activities, queues and resources. This allows for the modeling of scenarios

of unlimited complexity and in any field. Further, if the basic building elements are

not sufficient to a model a given situation, most systems also allow for the

integration of programming code in the form of user inserts or add-ons. Although

these systems prove extremely flexible and powerful from an academic stand point,

those who can benefit from its power the most, the industry practitioners, have not

embraced it. The generality and complexity of general purpose simulation systems

meant that industry members were forced to learn the equivalent of a new language

or hire an expensive simulation consultant to perform the required analysis. In the

construction industry, simulation can be most beneficial during the estimating stage

where limited time is available and costs incurred are typically not easily recovered

since only a small amount of estimates lead to a successful contract award.

Construction practitioners require a simulation tool that is easy to use and tailored to

their specific requirements with results that can be directly used as part of other

decision support systems such as computer estimating programs [11].

A linear programming model was presented by Mayer and Stark in 1981. In this

model the earthmoving costs were split into three components: costs for excavation,

costs for hauling, and costs for fill. These costs were linearly proportional to the

quantity of material to be handled. The cost of purchasing mil at the borrow pits

was also considered [12].

14

In 1982, Luch and Halpin presented a Simulation model called MicroCYCLONE.

MicroCYCLONE is a microcomputer based simulation program designed

especially for modeling and analyzing site level processes which are cyclic in

nature. In broader terms, it can be used to model construction operations which

involve the interaction of tasks with their related duration, and the resource unit

flow routes through the work tasks are the basic rationale for the modeling of

construction operations [13].

In the two models discussed above, cost rates were assumed constant. By

considering the variation in the unit cost of earthworks, an extension to the models

was proposed by Easa [14] in 1987. It was found that the major variation in the unit

cost of earthworks was the variation in the unit cost for purchasing and/or

excavating the soil at the borrow pits. Therefore, a stepwise unit cost function of

purchase and excavation for the borrow pits was modeled. Other cost components

were still assumed to be constant. A further modification was made to the stepwise

unit cost function by Easa [15] in 1988.

In 1988, Alkass and Harris designed a system to aid in equipment selection for road

construction. This system, ESEMPS, is an expert system [16].Expert systems

function by asking the user a series of yes/no questions. As these questions are

answered, a set of programmed rules allow the system to guide the user to the

―correct answer‖. This system is linked to a set of external databases which contain

information on machines, earth types, etc. The system also calculates projected

costs.

In 1989,Ioannou designed a Simulation UM-CYCLONE model. UM CYCLONE is

a discrete-event simulation system for construction operations based on activity

scanning and activity cycle diagrams and runs under DOS [17].

In 1992, Amirkhanian and Baker developed an expert system specifically geared

toward equipment selection. Their system, based in VP Expert, asks a series of

questions about project conditions and then recommends the type and number of

15

pieces of equipment needed. Equipment choices include dozers, scrapers,

excavators and trucks [18].

Hanna in 1994 created a similar system for crane selection. In this system, the most

appropriate type and size of crane or derrick is selected based on project parameters

such as heaviest lift, maneuverability, and job conditions. The program produces

output which lists the best type of crane, as well as setup parameters such as number

of lifts for a tower crane. The main focus of the system is to eliminate or reduce the

need for expensive consultations with crane experts. Results of the program were

positive, though limited by the available database [19].

In 1994, AbouRizk and Shi developed an optimization model that considers only

the quantities of resources being used along with their respective user-specified

boundaries. The system recommends a resource combination, within the specified

boundaries, closer to the optimum resource allocation [20].

In 1994, Huang et al. developed a DISCO Simulation model. The DISCO system

provides a graphical environment in which modeling and simulation of construction

operations can be conducted in an interactive fashion. The model developed for the

bridge construction and the results of the simulation are presented [21]. In the same

year Tommelein et al. designed a CIPROS which is a knowledge-based construction

planning simulation system that enables its users to formalize and test alternative

construction plans by relating project-specific design drawings and specifications to

a network of construction processes, elementary simulation process networks, and

associated resources [22].

In 1996, Christian and Xie developed an expert system built upon a rating system

for various types of equipment. A survey was sent out to experts in the field seeking

input on what type of machine was best for a variety of projects and soil types. This

information was compiled into a table that rated each type of equipment from 0 to

10 (10being best) for each set of project parameters. The expert system asks a set of

questions, and then uses the rating system to select the appropriate type and number

of equipment[23].

16

A STROBOSCOPE was proposed by Martinez in 1996. STROBOSCOPE is a

simulation system designed as the successor to UM-CYCLONE based on activity

scanning and activity cycle diagrams. The name STROBOSCOPE, an acronym for

state and resource-Based Simulation of construction processes, reflects the system's

major design objective: the ability to make complex dynamic decisions (and thus

control the simulation at run-time) based on the simulation system state and the

characteristics, attributes, and state of resources. Unlike other simulation systems,

STROBOSCOPE is based on three-phase activity scanning and not process

interaction. The activity scanning simulation paradigm makes STROBOSCOPE

better suited for modeling complex resource interactions such as those that

characterize cyclic operations where no distinction is made between resources that

serve (servers or scarce resources) and those served (customers or moving entities).

STROBOSCOPE simulation models use an easy-to-learn graphical network-based

representation similar to activity cycle diagrams [24]. In the same year Sawhney

and AbouRisk presented a HSM simulation system. HSM enhances and combines

the concepts of work breakdown structure and process modeling to arrive at an

advanced framework for planning [25].

Special purpose simulation (SPS) was proposed by AbouRizk and Hajjar in 1997 to

address the stated issues. The idea is to develop user friendly simulation tools native

to the application domain itself. This typically involves the development of custom

user interfaces, simulation engines, support libraries and integration modules. By

specializing, the full-fledged flexibility of a general purpose simulation tool is lost.

However, the resultant benefits far outweigh the limitations. SPS tools allow

industry practitioners to use simulation systems without prior knowledge of

simulation theory [26]. And after one year MaCabe introduced belief networks as a

diagnostic tool in order to obtain a near optimum solution, accounting for both the

quantity and capacity of each utilized resource [27].

In 1999, SIMPHONY simulation system was proposed by AbouRizk and Hajjar

which provides various services that enable the developer to easily control different

behaviors in the developed tool such as simulation behaviors, graphical

17

representation, statistics, and animation. These services allow building flexible and

user friendly tools in a relatively short time [28].

In 2000, Naoum and Haidar have developed a genetic algorithm model for the

equipment selection problem. Although their model satisfies the requirements for an

integer programming solution, the authors pursued a genetic algorithm solution. The

solution incorporates the lifetime discounted cost of the equipment, which is

formally attached to the assumption that the equipment is used from purchase until

official retirement age, and not sold or replaced before that time. The authors argue

that intelligent search techniques are necessary because integer programming is

incapable of solving a problem with more than one type of independent variable

[29]. In the same year Kannan et al. recognize that despite the complementary role

of academic research and industry applied simulation models, a gap exists between

the two: academia follow ―opportunity driven‖ models and industry aims for ―need-

based‖ models. The authors provide some defined requirements and ―success

factors‖ for simulation programming. A short but directed literature survey of

simulation modeling in the construction industry is also included [30].

In 2007, Bruno et al. propose a model using Stochastic Colored Petri Nets to

represent the operational dynamics of earth moving work. For this purpose, a

graphic and analytic model that represents the earth moving activities was idealized.

As a conclusion of this study, it can be stated that Petri nets models provide an

important instrument for decision makers when managing earth moving planning

and execution [31]. In 2008, Kapur et al. presented a new methodology for

integration of ‗variable productivity‘ data with a visualization model of earthwork

operations. The paper presents a prototype of a 4D visualization model which is

designed by integrating the road design data, quantities of cut and fill, productivity

model, algorithms for modeling terrain surfaces and a progress profile visualize.

The model generates automatically terrain surfaces of progress profiles for

earthwork operations and visualizes progress profiles throughout the construction

operations under different site and soil conditions. It is demonstrated with a real life

case study in a road project [32].

18

Finally Table 2.1 illustrates summary of the previous published models in the same

field of study.

Table 2.1: PROEQUIP and previous published models for earthmoving

n Reference Model concept

and name

Description and Function

1 Willenbrock [10] Simulation (GPSS) to estimate cost for earthworks

2 Halpin [11] Simulation

(CYCLONE)

Allows the graphical representation and

simulation of discrete systems that deals with

deterministic or stochastic variables by dividing

the construction process into work tasks

3 Mayer and Stark

[12]

Linear

programming

model

Estimate excavation, hauling and fill cost

4 Luch and Halpin

[13]

Simulation

(MicroCYCLONE)

MicroCYCLONE is a microcomputer based

simulation program designed specially for

modeling and analyzing site level processes which

are cyclic in nature. In broader terms, it can be

used to model construction operations which

involves the interaction of tasks with their

related duration, and the resource unit flow

routes through the work tasks are the basic

rationale for the modeling of construction

operations.

5 Easa [14] Mathematical

model

Modification and improvement in unit cost

calculations

6 Easa [15] Mathematical

model

New modifications and improvement in unit cost

calculations

7 Alkass and Harris

[16]

Expert system

(ESEMPS)

Aid system using for selecting the road

construction equipment based on production rate

8 Ioannou [17] Simulation (UM-

CYCLONE)

UM CYCLONE is a discrete-event simulation

system for construction operations based on

activity scanning and activity cycle diagrams.

UM CYCLONE runs under DOS

19

9 Amirkhanian and

Baker [18]

Expert system Aid system using for selecting the equipment

based on productivity for dozers, scrapers,

excavators and trucks

10 Hanna [19] Mathematical

model

Selection the appropriate type and size of crane

base on project parameters

11 Rizk and Shi [20] Mathematical

model

Advice the optimum resource allocation in

construction sites

12 Huang et al. [21] Simulation

(DISCO)

The DISCO system provides a graphical

environment in which modeling and simulation

of construction operations can be conducted in

an interactive fashion. The model developed for

the bridge construction and the results of the

simulation are presented.

13 Tommelein et al.

[22]

Simulation

(CIPROS)

CIPROS is a knowledge-based construction

planning simulation system that enables its users

to formalize and test alternative construction

plans by relating project-specific design

drawings and specifications to a network of

construction processes, elementary simulation

process networks, and associated resources.

14 Christian and Xie

[23]

Expert system Advice the best type of machine for variety of

projects using rating system

15 Martinez [24] Simulation

(STROBOSCOPE)

STROBOSCOPE is a simulation system designed

as the successor to UM-CYCLONE. Based on

activity scanning and activity cycle diagrams.

16 Sawhney and

AbouRisk [25]

Simulation (HSM) HSM enhances and combines the concepts of

work breakdown structure and process modeling

to arrive at an advanced framework for

planning.

17 AbouRizk and

Hajjar [26]

Simulation (SPS) Selecting the equipment based on productivity

18 MaCabe [27] Network model

(MaCabe)

Diagnostic tool to obtain a near optimum solution

according for both quantity and capacity of each

20

resource

19 AbouRizk and

Hajjar [28]

Simulation

(SIMPHONY)

provides various services that enable the

developer to easily control different behaviors in

the developed tool such as simulation behaviors,

graphical representation, statistics, and animation.

These services allow building flexible and

userfriendly tools in a relatively short time.

20 Naoum and

Haidar [29]

Genetic algorithm Selecting the equipment based on life time

discounted cost

21 Kannan et al.

[30]

simulation Selecting the earthmoving equipment based on

literature survey

22 Bruno et al. [31] Stochastic colored

Petri nets

Instrument for planning earthmoving using

graphic and analytic model using productivity

results

23 Kapur et al. [32] new methodology

for integration of

‗variable

productivity‘ data

with a visualization

model

4D visualization model which is designed by

integrating the road design data, quantities of

cut and fill, productivity model, algorithms for

modeling terrain surfaces and a progress profile

visualize. The model generates automatically

terrain surfaces of progress profiles for

earthwork operations and visualizes progress

profiles throughout the construction operations

under different site and soil conditions.

24 Hassan Eliwah Simulation

(PROEQUIP)

It is an aid system using for earthmoving

equipment selection based on equipment

production rate only or equipment unit cost

only or equipment production rate and

equipment unit cost together.

CCHHAAPPTTEERR TTHHRREEEE

EEAARRTTHHMMOOVVIINNGG OOPPEERRAATTIIOONNSS

22

CCHHAAPPTTEERR 33

EEAARRTTHHMMOOVVIINNGG OOPPEERRAATTIIOONNSS


The function of heavy earthmoving equipment is to move or assist in the moving of

soil and rock from point A to point B. The purchase of this equipment constitutes a

particularly large investment on the part of the buyer. One cannot get into the

business of owning this type of equipment without substantial cash reserves and/or

financial backing. Regarding to that it is important that the reader have an

understanding of basics concerning the construction equipment. This section will

provide an introduction to the principles and vernacular of the field. The discussion

will cover in general the hydraulic excavator and hauler equipment.

33..22 MMAANNAAGGIINNGG EEAARRTTHHMMOOVVIINNGG OOPPEERRAATTIIOONNSS

The management of construction equipment is a difficult task. Equipment managers

are often called upon to make complex economic decisions involving the machines

in their charge. These decisions include those concerning acquisitions, maintenance,

repairs, rebuilds, replacements, and retirements. The equipment manager must also

be able to forecast internal rental rates for their machinery. Repair and maintenance

expenditures can have significant impacts on these economic decisions and

forecasts [33].

Managers must follow basic management phases to ensure that projects successfully

meet deadlines set forth in project directives. Additionally, managers must ensure

conformance to safety and environmental-protection standards. The basic

management phases are planning, organizing, staffing, directing, controlling and

executing [33].

23

Proper equipment selection is crucial to achieving efficient earthmoving and

construction operations. Consider the machine‘s operational capabilities and

equipment availability when selecting a machine for a particular task. The manager

should visualize how best to employ the available equipment based on soil

considerations, zone of operation, project-specific requirements, equipment total

cost and equipment productivity. Productivity estimates, productivity control, and

productivity records are the basis for management decisions. Therefore, it is helpful

to have a common method of recording, directing, and reporting production [34].

33..22..11 SSaaffeettyy

Engineers and safety officers are responsible for ensuring that personnel follow

safety standards. Time is usually the controlling factor in construction operations in

the theater of operations. The necessity for economy of time, coupled with the

temporary nature of much of the work, sometimes results in safety precautions that

are substantially lower than those used in civilian practice, but this does not mean

safety can be ignored.

Do not construe the lack of documentation of hazards as an indication of their

nonexistence or insignificance. Where safety precautions are necessary but are not

documented, or where existing precautions are judged to be inadequate, the

commanding officer must issue new or supplementary warnings. Each job has its

own particular safety hazards. Identify dangers and prepare a safety program to

reduce or eliminate all hazards. Supervisors must conduct all operations following

the guidance in the safety program [35].

The appropriate sections of safety manual identify safety rules for specific

equipment. Also, check applicable technical and operator manuals prior too perating

all equipment. Some general safety rules are as follows [35]:

Inspect equipment before use, and periodically on a regular basis.

Ensure that mechanized equipment is operated by qualified and authorized

personnel only.

Use seat belts when they are available.

24

Provide barriers to prevent personnel from walking under loading equipment

that has a hoist or lift capability.

Operate equipment in a manner that will not endanger persons or property.

Observe safe operating speeds.

Shut down and turn off the engine when equipment is unattended.

Stop the equipment completely (apply the parking brake if available) before

mounting or dismounting.

Do not operate any machinery or equipment for more than 10consecutive

hours without an 8-hour rest interval.

Post the safe load capacities at the operator's position on all equipment not

rigged to prevent overloading.

Post the safe operating speeds at the operator‘s position on all equipment not

having a speed governor.

Ensure that only the operator is on the equipment while it is running.

Supervisors can authorize exceptions in emergency situations, some training

situations, and when required for maintenance.

Shut down and turn off the engine when refueling motor vehicles and

mechanized equipment.

Before using a machine, a qualified, licensed operator should inspect and test the

equipment to determine its safe operating condition. Equipment operator

maintenance checks, service charts, and common sense ensure safe operation and

proper maintenance. Tag any unsafe machinery or equipment ―Out of Service, Do

Not Use‖ at the operator's position, to prevent its use until repaired. Ensure that the

equipment‘s safety features (backup alarms, lights, and so on) are operational [35].

For special repair and maintenance procedures follow those items: [35]

Shut down or lock out equipment controls while a machine is being repaired,

adjusted, or serviced.

Position the equipment in a place, away from the project area, that is safe for

the mechanic to work.

25

Crib or block suspended machinery, equipment, or parts, and machines held

apart by slings, hoists, or jacks. Do not work underneath or between items

not properly blocked.

Lower blades, bowls, hooks, buckets, and forks to the ground or onto

suitable blocking material when equipment is undergoing maintenance or

repairs.

When operating equipment at night

Equip all mobile equipment with adequate headlights and taillights.

Keep construction roads and working areas well illuminated until all workers

have left the area.

Ensure that signalers, spotters, inspectors, maintenance personnel, and others

who work in dark areas exposed to vehicular traffic wear reflector zed vests

or other such apparel if the tactical situation permits.

When excavating

Shore, brace, or slope excavations that are more than 4 feet deep, unless

working in solid rock, hard shale, hardpan, cemented sand and gravel, or

other similar materials.

Design shoring and bracing to be effective all the way to the bottom of the

excavation.

Use sheet piling, bracing, shoring, trench boxes, or other methods of

protection, including sloping, based upon calculation of the pressures exerted

by and the condition and nature of the materials being retained.

Provide additional shoring and bracing to prevent slides or cave-ins when

excavating or trenching in locations adjacent to back-filled excavations or

when subjected to vibrations from traffic, vehicles, or machinery.

26

33..33 HHYYDDRRAAUULLIICC EEXXCCAAVVAATTOORRSS

Hydraulic excavators (back hoe) are designed to excavate below the ground surface

on which the machine rests. These machines have good mobility and are excellent

for general-purpose work, such as excavating trenches and pits. Because of the

hydraulic action of their stick and bucket cylinders, they exert positive forces

crowding the bucket into the material to be excavated. The major components of the

hydraulic hoe are the boom, the stick (arm), and the bucket. Fast-acting, variable-

flow hydraulic systems give hydraulic excavators high implement speed and

breakout force to excavate a variety of materials.

There are many variations in hydraulic excavators. They may be either crawler or

rubber-tire-carrier-mounted, and there are many different operating attachments.

With the options in types, attachments, and sizes of machines, there are differences

in appropriate applications and therefore variations in economical advantages [33].

Hydraulic power is the key to the advantages offered by these machines. The

hydraulic control of machine components provides: [33] faster cycle times,

Outstanding control of attachments, High overall efficiency, Smoothness and ease

of operation and Positive control that offers greater accuracy and precision.

Hydraulic excavators are classified by the digging motion of the hydraulically

controlled boom and stick to which the bucket is attached. A downward arc unit is

classified as a "hoe" [33]. To calculate the productivity of the excavator as a

separate unit (not as an earthmoving system) use equation (3.1) [33]:

Productivity = (3600 sec x Q x F x AS:D/t) x (E/60 min hr) x (1/VC) (3.1)

where

Q = heaped bucket capacity (Lcm), F = bucket fill factor, AS:D = angle of swing

and depth (height) of cut correction, t = cycle time in seconds (table 3.3), E =

efficiency (min per hour), VC = volume correction for loose volume to bank

volume

27

The main factors affect on excavators selection are (1) the cost per cubic meter of

material excavated and (2) the job conditions under which the excavator will

operate [33].

Unless the application calls for a lot of travel to, from, and around the job sites, a

track-type excavator could be the better choice. Track-type excavators provide good

traction and flotation in almost all kinds of underfoot conditions. Consistently good

drawbar power provides excellent maneuverability. The tracked undercarriage also

provides good overall stability. If the job calls for frequent machine repositioning, a

track-type excavator will provide better operating efficiency where raising and

lowering outriggers would take extra time (see Figure 3.1) [1].

A Wheel Excavator (see Figure 3.2) combines traditional excavator features such as

360° swing, long reach, deep digging depth, high loading height, high digging

forces and high lift capacities, with the mobility of a wheeled undercarriage. The

rubber tires allow the excavator to travel paved roads, work in shopping malls,

squares, parking lots and other paved areas without damaging the pavement. Its

mobility allows fast independent travel between jobsites as well as on the jobsite

giving you more job planning flexibility [1].

Excavator buckets are rated to conform to both PCSA standard No. 3 (Power Crane

and Shovel Association - Mobile Hydraulic Excavator Standards) and SAE standard

J-296 (Society of Automotive Engineers, Inc. - Excavator, Mini-Excavator, and

Backhoe Hoe Bucket Volumetric Rating) where the buckets are rated on both their

struck and heaped capacities as follows [1]:

Struck Capacity: Volume actually enclosed inside the outline of the side plates and

rear and front bucket enclosures without any consideration for any material

supported or carried by the spill plate or bucket teeth [1]. Heaped Capacity: Volume

in the bucket under the strike off plane plus the volume of the heaped material

above the strike off plane, having an angle of repose of 1:1 without any

consideration for any material supported or carried by the bucket teeth (see Figure

3.3 and Figure 3.4) [1].

28

Figure 3.1 Hydraulic hoe loading

a truck. Figure 3.2 Wheel-mounted hydraulic hoe.

Figure 3.3 Basic parts of a hydraulic hoe

Figure 3.4 Hydraulic hoe

bucket capacity rating

dimensions.

To maximize production of the earthmoving system, do the following:

Ideal Bench Height and Truck Distance: For stable or consolidated materials, bench

height should be about equal to stick length. For unstable materials it should be less.

The most useful truck position is when the inside truck body rail is below the boom

stick hinge pin [1].

Optimum Work Zone and Swing Angle: For maximum production, the work zone

should be limited to 15° either side of machine center or about equal to

29

undercarriage width. Trucks should be positioned as close as possible to machine

centerline [1].Best Distance from the Edge; the machine should be positioned so

that the stick is vertical when the bucket reaches full load. If the unit is farther back,

breakout force is reduced. If it is closer to the edge, undercutting may occur and

time is wasted bringing the stick back out (see Figure 3.5) [1].

Figure 3.5 Maximize production of the earthmoving system

30

33..44 TTRRUUCCKKSS AANNDD HHAAUULLIINNGG OOPPEERRAATTIIOONNSS

Since the 1930s most of the material moved out of open cut mines/quarries has been

hauled by motorized trucks [33]. Whereas in underground mines material moved

along the haulage drives has been in rail mounted trucks pushed or pulled by

locomotives, and in recent times motorized truck haulage has been introduced

underground. Trucks are hauling units that provide relatively low hauling costs

because of their high travel speeds. The weight capacity of a truck may limit the

volume of the load that a unit may haul. The productive capacity of a truck depends

on the size of its load and the number of trips it can make in an hour.

In transporting excavated material, processed aggregates, and construction

materials, and for moving other pieces of construction equipment (see Figure3.6),

trucks serve one purpose: they are hauling units that, because of their high travel

speeds, provide relatively low hauling costs. The use of trucks as the primary

hauling unit provides a high degree of flexibility, as the number in service can

usually be increased or decreased easily to permit modifications in the total hauling

capacity of a fleet. Most trucks may be operated over any haul road for which the

surface is sufficiently firm and smooth, and on which the grades are not excessively

steep. Some units are designated as off-highway trucks because their size and

weight are greater than that permitted on public highways (see Figure3.7). Off-

highway trucks are used for hauling materials in quarries and on large projects

involving the movement of substantial amounts of earth and rock. On such projects,

the size and costs of these large trucks is easily justified because of the increased

production capability they provide [33].

Trucks can be classified by many factors, including [33]

1. The method of dumping the load rear-dump, bottom-dump, or side-dump.

2. The type of frame rigid-frame or articulated.

3. The size and type of engine gasoline, diesel, butane, or propane.

4. The kind of drive, for example two wheel

5. The number of wheels and axles

31

6. The class of material hauled, for example rock material

7. The capacity

8. The type of work

Trucks are classified under the type of work [1]:

Rigid Frame Trucks: for use in hauling many types of materials

(see Figure3.8). The shape as the extent of sharp angles and

corners.

Articulated Trucks: specifically designed to operate over rough

soft ground, and in confined working locations where a rigid-

frame truck would have problems (see Figure3.9, Figure 3.10)

Off-highway dump truck: the body floor slopes forward at a slight

angle, typically less than 15° (see Figure3.11, Figure 3.12).

Some of the current day manufacturers include: Komatsu, Terex, Unit Rig, Pay-

hauler, Caterpillar, Euclid, Wabco, Bell, Liebherr, Tamrock [Toro], Atlas Copco-

Wagner, Elphinstone and many others that have developed units for specific

markets eg. The ―Kiruna‖ underground electric truck.

Figure 3.6 Truck tractor unit towing Figure 3.7 Off-highway truck

32

Figure 3.8 Highway rigid-frame rear-

dump truck Figure 3.9 An articulated dump truck

Figure 3.10 An articulated dump truck

moving through soft ground

Figure 3.11 Off-highway tractor

towing a loaded bottom-dump

trailer

Figure 3.12 Highway bottom-dump

33

There are at least three methods of rating the capacities of trucks and wagons: [33]

1. Gravimetric: the load that it will carry, expressed as a weight.

2. Struck volume: the volumetric amount it will carry, if the load was water

level in the body (see Figure3.13).

3. Heaped volume: the volumetric amount it will carry, if the load was heaped

on a 2:1 slope above the body (see Figure3.13).

Figure 3.13 Measurement of volumetric capacity

The productive capacity of a truck depends on the size of its load and the number of

trips it can make in an hour. The number of trips completed per hour is a function of

cycle time. Truck cycle time has four components: (1) load time, (2) haul time, (3)

dump time, and (4) return time. Examining a match between truck body size and

excavator bucket size yields the size of the load and the load time. The haul and

return cycle times will depend on the weight of the vehicle, the horsepower of the

engine, the haul and return distance, and the condition of the roads traversed. Dump

time is a function of the type of equipment and conditions in the dump area [33].

CCHHAAPPTTEERR FFOOUURR

EESSTTIIMMAATTIINNGG TTEECCHHNNIIQQUUEESS

35

CCHHAAPPTTEERR 44

EESSTTIIMMAATTIINNGG TTEECCHHNNIIQQUUEESS


Earthmoving is the removal of existing material, which includes excavating or

loading, transporting, grading and unloading materials. The productivity, or output,

of earthmoving equipment can be defined as the total amount of material handled by

a machine in a certain time [7]. In estimating productivity, the basic element needed

to be analyzed is the productivity rate which is the amount of material a machine

can handle in a unit time such as a minute or an hour. In this chapter, significant

productivity factors common to different types of machines are first discussed.

Following this, the factors influencing the productivity rates of specific types of

machines are discussed. Problems in estimating machine productivity are

determined and a model for adjusting productivity estimates is also proposed.

There are two aspects to be considered in judging the appropriateness of a machine

for a particular job. One is its technical applicability, including productive capacity;

and the other is its economic feasibility [34]. In order to select appropriate

machines, machine performance is usually used as a criterion and judged by

estimating the unit costs which are costs spent on handling materials per unit

volume. Estimating costs is a difficult task in earthmoving planning, and in reality

construction organizations use different approaches to classify and calculate costs.

This chapter discusses the productivity and cost estimating of earthmoving

equipment and factors influencing productivity. The main elements of the costs are

analyzed and methods for calculating the costs are presented.

36

44..22 PPRROODDUUCCTTIIVVIITTYY EESSTTIIMMAATTIINNGG

The most convenient and useful unit of work done and unit of time to use in

calculating productivity for a particular piece of equipment or a particular job is a

function of the specific work-task being analyzed. To make accurate and

meaningful comparisons and conclusions about production, it is best to use

standardized terms [33].

Depending on where a material is considered in the construction process, during

excavation versus after compaction, the same material weight will occupy different

volumes (Figure 4.1). Material volume can be measured in one of three states:

Bank cubic meter (BCM): A BCM is 1 cubic meter of material as it lies in

its natural/undisturbed state.

Loose cubic meter (LCM): A LCM is 1 cubic meter of material after it has

been disturbed by an excavation process.

Compacted cubic meter (CCM): A CCM is 1 cubic meter of material after

compaction.

Figure 4.1 Material-Volume Changes Caused by Construction Processes

When manipulating the material in the construction process, its volume changes.

(Tables 4.1, gives material-volume conversion and load factors [7]) The prime

question for an earthmover is about the nature of the material‘s physical properties;

for example, how easy is it to move? For earthmoving operations, material is placed

in three categories—rock, soil (common earth), and unclassified.

37

Table 4.1 Material Volume Conversion Factors

Most earth and rock materials swell when removed from their natural resting place.

The volume expands because of voids created during the excavation process. After

establishing the general classification of a soil, estimate the percentage of swell.

The quantity of material to be handled in an operation generally does not have a

direct influence on the productivity rates of individual machines. When the duration

of an operation has been set, however, it is a factor that should obviously be

considered in determining the size and number of machines for the overall

productivity of a fleet. In relation to the quantity, the physical state of the material is

important for estimates. When material is in its undisturbed normal state, it is

referred to as in situ, or bank, material, and usually occupies a fixed volume known

as the in situ volume or bank volume. After king excavated from its original

location, the volume of material expands due to the breakup of its naturally

compressed part. The material is then in a loose state and its volume is known as the

loose volume. The volume of a material varies from one state to the other, and has

great impact on the productivity rates. Therefore, the system requires users to input

what type of measure they take in estimating quantities. When users estimate the

volume of a soil to be handled in the bank state, the system converts it into the loose

38

volume since earthmoving machines actually handle mils in the loose state. When

calculating productivity, it should always be tried to get an accurate measure of

actual material weights and swell factor. Any companies or contractors which move

material will usually calculate productivity in ton per cubic meter. Earthmoving

contractors will usually get paid by the moved number of cuyd bank or m3 bank.

During the productivity estimating, some factors should considered such Fill Factor

Ratio between nominal volume and actual volume of a bucket or the body of a

dump truck, given as percentage of nominal volumeand Load Factor: Converts the

nominal payload volume of a dump truck (in loose cuyd or m3) into the effective

loaded volume in bank cuyd or m3. Most material codes define the load factor LF

as LF = Swell Factor SF x Fill Factor FF. Depending on the digging action of the

equipment and the operational conditions, a excavator may under-fill or over-fill its

bucket. This condition is measured by the bucket fill factor (ff) [34].

Bucket fill

factor (ff) =

loose vol. of material excavated in an average load

nominal bucket capacity, Bc (4.1)

Typical ff‘s for digging condition [34]: Easy: 1.0-1.2 or Medium:0.8-1.0 or Hard:

0.6-0.9. The bucket factor is a combination of swell factor and (ff). It enables the

bucket capacity in terms of volume of material in BCM to be readily calculated.

Bucket factor, Bf bucket fill factor

swell factor (4.2)

So that:

Bucket capacity (BCM) = nominal bucket capacity (Bc) x bucket factor

(Bf) (4.3)

The cycle time of excavator is the time taken to fill the bucket, swing the boom

round to the dump position, dump the bucket-load into the truck or hopper and

swing back to the digging position. For planning purposes, cycle times can be

estimated from manufacturer‘s literature or time studies. Operator skill is an

important factor. Table 4.2 lists a range of excavator cycle times [33].

39

Table 4.2: Loading excavator cycle times for a 90o swing (seconds)

Digging Conditions

Capacity

(Bm3)

Easy Medium Medium-

Hard

Hard

3

3

5

5.5

6

8

9

11.5

15

19

35

18

20

21

21

22

23

24

26

27

29

30

23

25

26

26

27

28

28

30

32

34

36

28

29

30

30

31

32

32

33

35

37

40

32

33

34

34

35

36

37

38

40

42

45

Where easy digging - loose material e.g., sand, small gravel. Medium digging,

partially consolidated materials e.g., clayey gravel, packed earth, anthracite.

Medium-Hard - well blasted lime-stones, heavy & wet clays, weaker ores, gravel

with large boulders. Hard - materials that require heavy blasting and tough plastic

clays, eg, granite, strong limestone, taconite, strong ores [33].

Excavator cycle times are normally based on a 90o swing (S = 1). Obviously as the

swing angle increases, the cycle time will increase. The cycle time can be modified

accordingly by including a swing factor and typical values are listed in Table 4.3

[33].

Express swell as a percentage increase in volume (Table 4.4). For example, the

swell of dry clay is 35 percent, which means that 1 cubic meter of clay in the bank

40

state will fill a space of 1.35 cubic meters in a loosened state. Estimate the swell of

a soil by referring to a table of material properties such as Table 4.4.

In earthmoving work, it is common to compact soil to a higher density than it was in

its natural state. This is because there is a correlation between higher density and

increased strength, reduced settlement, improved bearing capacity, and lower

permeability. The project specifications will state the density requirements.

Soil weight affects the performance of the equipment. To estimate the equipment

requirements of a job accurately, the unit weight of the material being moved must

be known. Soil weight affects how dozers push, excavator load and truck load the

material. Assume that the volumetric capacity of a truck is 14 cubic meters and that

it has a rated load capacity of 20,000kgs. If the material being carried is relatively

light (such as cinder), the load will exceed the volumetric capacity of the truck

before reaching the gravimetric capacity. Conversely, if the load is gravel (which

may weigh more than 3,000 kgs per cubic meter), it will exceed the gravimetric

capacity before reaching the volumetric capacity [7].

NOTE: The same material weight will occupy different volumes in BCM,

LCM, and CCM. In an earthmoving operation, the basic unit of comparison is

usually BCM. Also, consider the material in its loose state (the volume of the

load). Table 4.4 gives average material conversion factors for earth-volume

changes.

Use a load factor (see Table 4.4) to convert the volume of LCM measured to BCM

measured (LCM x load factor = BCM). Use similar factors when converting

material to a compacted state. The factors depend on the degree of compaction.

Compute the load factor as follows:

If 1 cubic meter of clay (bank state) = 1.35 cubic meters of clay (loose state), then 1

cubic meter of clay (loose state) = 0.74 cubic meter of clay (bank state).

In this case, the load factor for dry clay is 0.74. This means that if a scraper is

carrying 25 LCM of dry clay, it is carrying 18 BCM (25 x 0.74).

41

Table 4.3: Excavator swing factors

Angleof swing 45 60 75 90 120 150 180

Swing factor 1.20 1.10 1.05 1.00 0.91 0.84 0.77

Table 4.4: Weight of Materials according to German Norm DIN/VOB

Weight of materials * bank

lb/cuyd/kg/m3 swell in %

swell

factor

loose

lb/cuyd/kg/m3

Clay - natural bed 3400/2020 22 0.82 2800/1660

dry 3100/1840 24 0.80 2500/1480

wet 3500/2080 24 0.80 2800/1660

Clay with gravel - dry 2800/1660 17 0.86 2400/1420

wet 3100/1840 19 0.84 2600/1540

Decomposed rock 75% rock, 25% earth 4700/2790 42 0.70 3300/1960

50% rock, 50% earth 3850/2280 33 0.75 2900/1720

25% rock. 75% earth 3300/1960 24 0.80 2650/1570

Earth - dry packed 3200/1900 26 0.79 2550/1510

wet excavated 3400/2020 26 0.79 2700/1600

loam 2600/1540 23 0.81 2100/1250

Granite - broken 4600/2730 64 0.61 2800/1660

Gravel - pitrun 3650/2170 12 0.89 3260/1930

dry 2850/1690 12 0.89 2550/1510

Limestone - broken 4400/2610 69 0.59 2600/1540

crushed ----- ----- ----- 2600/1540

Sand - dry, loose 2700/1600 12 0.89 2400/1420

damp 3200/1900 12 0.89 2850/1690

wet 3500/2080 13 0.88 3100/1840

Sand with clay - loose 3400/2020 26 0.79 2700/1600

compacted ----- ----- ----- 4050/2400

Excavator productivity [7]

Qs = Bc Bf C Sf A O (PTF) (4.4)

Where: Qs=excavator productivity (Bm3/hr), Bc =nominal bucket capacity (m

3),

Bf=bucket factor, C=theoretical cycles/hr for a 90o swing = 60/tc, tc=excavator cycle

time for a 90o swing (mins), Sf=swing factor, A=mechanical availability during

scheduled hours of work, O=job operational factor and PTF=propel time factor.

Note: actual bucket capacity (B) = nominal bucket capacity (Bc) * bucket factor (Bf)

(Bm3)

42

Truck Productivity [7]

Let: Rated truck load, = Lt tons

Average material density = t/m3

Excavator bucket capacity = B m3

1. Number of passes required to load the truck = L

x B

t

(4.5)

2. Multiply by the excavator cycle time to obtain the time required to load the truck,

tL

3. Estimate the haul distances within the pit and from the top of the pit to the

ore/waste dumps.

4. Select suitable truck speeds for travelling up-grade loaded, on a level grade

loaded and empty and down-grade, empty. These speeds may be obtained from

charts and tables provided by the manufacturer; tup, tlevel1, tlevel2, tdown.

5. Estimate the time required to spot a truck at a shovel, ts.

6. Sum the above times to obtain the total truck cycle time, Tct

Tct = tL + tup + tlevel1 + tlevel2 + tdown + ts mins (4.6)

Number of truck cycles per hour = 60

Tct (4.7)

Truck productivity, Qt = L x Tt

ct

60

(4.8)

43

The haul distance is a major determinant of productivity rates for the simple reason

that with the increase of the length of haul distance, the time a machine spends on

the haul and return route generally increases, and its productivity rate decreases.

The total resistance is a major factor influencing productivity rates, since it could

slow down the travel speed of a machine [7]. We can describe the total resistance as

a summation of the grade and running resistance; Grade Resistance is a measure of

the force that must be overcome to move a machine over unfavourable grades

(uphill), grade assistance is a measure of the force that assists machine movement

on favourable grades (downhill), grades are generally measured in percent slope,

which is the ratio between vertical rise or fall and the horizontal distance in which

the rise or fall occurs [7]. For example, a 1% grade is equivalent to a 1 m rise or fall

for every 100 m of horizontal distance; a rise of 4.6 m in 50 m equals a 9.2% grade.

Rolling Resistance (RR) is a measure of the force that must be overcome to roll or

pull a wheel over the ground. It is affected by ground conditions and load, the

deeper a wheel sinks into the ground, the higher the rolling resistance, Internal

friction and tire flexing also contribute to rolling resistance, Experience has shown

that minimum resistance is approximately 2% (1.5% for radial tyres or dual tyred

trucks) of the gross machine weight (on tyres) or Resistance due to tire penetration

is approximately 0.6% for each cm of tire penetration [7].Thus rolling resistance

can be calculated using these relationships in the following manner: RR equal two

percent of GMW plus 0.6 percent of GMW per cm tire penetration [7]. In terms of

newtons it‘s a resistance per hundred kilograms of gross weight – from table of

rolling resistance in newtons per thousand kilograms of gross weight of various

road surfaces (Table 4.5) -. Other methods are derived from this basic expression.

Total resistance can also be represented as consisting completely of grade resistance

expressed in percent grade. In other words, the rolling resistance component is

viewed as a corresponding quantity of additional adverse grade resistance. This can

be done by converting the contribution of rolling resistance into a corresponding

percentage of grade resistance. Since 1% of adverse grade offers a resistance of 10

44

kg for each metric ton of machine weight, then each 10 kg resistance per ton of

machine weight can be represented as an additional 1% of adverse grade.

Table 4.5: ROLLING RESISTANCE FACTORS

Under-footing

Rolling Resistance Percent

Tyres

Bias Radial

Track Track+

Tyres

Very hard, smooth roadway, concrete, cold

asphalt, no penetration or flexing

1.5% 1.2% 0% 1.0%

Hard, smooth stabilised surfaced roadway no

penetration under load, watered, maintained

2.0% 1.7% 0% 1.2%

Dirtroadway, rutted under load, little

maintenance, no watering,25mm tyre

penetration

4.0% 4.0% 0% 2.4%

Rutted dirt roadway, soft under travel, no

maintenance, no stabilization, 100mm tyre

penetration or flexing

8.0% 8.0% 0% 4.8%

Very soft, muddy, rutted roadway 300mm tyre

penetration, no flexing

20% 20% 8% 15%

Various tyre sizes and inflation pressures will greatly reduce or increase the rolling

resistance. The values in this table are approximate, particularly for the track and

track + tyre machines. These value scan be used for estimating purposes when

specific performance information on particular equipment and given soil conditions

is not available [7].

By operating a machine skill-fully, a better operator usually spends less time on

activities and this yields higher production. The production correction factor due to

theski11 level of an operator can approximately be given as in Table 4.6 [1].

In routine operations, there is a certain amount of time spent on non-productive

activities. To estimate the actual output produced in the productive time, job

45

efficiency is often used to indicate the productive time as a fraction of the total time

spent. The job efficiency is usually expressed as a percentage of productive time in

minutes per hour (Table 4.7 and 4.8) [34]. In this research, it is assumed that the job

efficiency covers al1 minor idle or delay times, and other miscellaneous times, etc.

Table 4.6: Operator Skill Factor, FO

Table 4.7: Job Efficiency Factor, Fe

Table 4.8: Excavator operating efficiency

Management Conditions

Job

conditions

Excellent Good Fair Poor

Excellent

Good

Fair

Poor

0.83

0.76

0.72

0.63

0.80

0.73

0.69

0.61

0.77

0.70

0.66

0.59

0.70

0.64

0.60

0.54

46

From all the previous data, we can calculate the truck productivity as the following:

Step 1: Number of Bucket Loads: The first step in analyzing truck production is to

determine the number of excavator bucket loads it takes to load the truck [33].

Balanced number of bucket loads = (Truck capacity (Lcm)) /

(Bucket capacity (Lcm)) (4.9)

Step 2: Load Time: The actual number of bucket loads placed on the truck should

be an integer number. If one less bucket load is placed on the truck, the loading time

will be reduced; but the truckload is also reduced. Sometimes job conditions will

dictate that a fewer number of bucket loads be placed on the truck, i.e., the load size

is adjusted if haul roads are in poor condition or if the trucks must traverse steep

grades [33]:

Load time = Number of bucket swings X bucket cycle time (4.10)

Truckload (volumetric) = Number of bucket swings * volume of the

bucket (4.11)

If the division of truck body volume by the bucket volume is rounded to the next

higher integer and that higher number of bucket swings is used to load the truck,

excess material will spill off the truck. In such a case, the loading duration the

bucket cycle time multiplied by the number of bucket swings. But the volume of the

load on the truck equals the truck capacity, not the number of bucket swings

multiplied by the bucket volume [33]:

Truckload (gravimetric) = Volumetric (Lcm) * unit weight (loose vol.

kg/Lcm) (4.12)

Check: Truckload gravimetric < Rated gravimetric payload

Step 3: Haul Time: Hauling should be at the highest safe speed and in the proper

gear. To increase efficiency, use one-way traffic patterns. Based on the gross weight

of the truck with the load, and considering the rolling and grade resistance from the

47

loading area to the dump point, haul speeds can be determined using the truck

manufacturer‘s performance chart (see Figure 4.2) [1]

Haul time (min) = (Haul distance (m)) / (60 * 1000 * Haul speed

(km/hr)) (4.13)

Figure 4.2 Performance chart for Caterpillar 793C Truck

The chart should be used to determine the maximum speed for each section of a

haul road having a significant difference in grade or rolling resistance. While a

performance chart indicates the maximum speed at which a vehicle can travel, the

vehicle will not necessarily travel at this speed. Before using a performance chart

speed in an analysis, always consider such factors as congestion, narrow roads, or

traffic signals, when hauling on public roads, because these can limit the speed to

less than the value given in the chart [33].

Step 4: Return Time: Based on the empty vehicle weight, rolling and grade

resistance from the dump point to the loading area, return speeds can be determined

using the truck manufacturer's performance chart:

48

Return time (min) = (Return distance (m)) / (60 * 1000 * Return

speed (km/hr)) (4.14)

Step 5: Dump Time: Dump time will depend on the type of hauling unit and

congestion in the dump area. Consider that the dumping area is usually crowded

with support equipment. Total dumping time in such cases can exceed 2 min. After

dumping, the truck normally turns and returns to the loading area. Under favorable

conditions, a rear-dump can dump and turn in 0.7 min but an average unfavorable

time is about 1.5 min. Bottom-dumps can dump in 0.3 min under favorable

conditions, but they too may average 1.5 min when conditions are unfavorable [33].

Step 6: Truck Cycle Time: The cycle time of a truck is the sum of the load time,

the haul time, the dump time, and the return time (Table 4.3):

Truck cycle time = Load time + Haul time + Dump time + Return time (4.15)

Figure 4.3 Basic truck load cycle.

49

Step 7: Number of Trucks Required: The number of trucks required to keep the

loading equipment working at capacity:

Number of trucks = (Truck cycle time (min)) / (Load time (min)) (4.16)

Step 8: Productivity: The number of trucks must be an integer number, so if an

integer number of trucks lower than the result of Eq. (4.16) is chosen then the trucks

will control production

Productivity (Lcm/hr) = Truck load (Lcm) * Number trucks * (60 min

/ Truck cycle time (min)) (4.17)

When an integer number of trucks greater than the result of Eq. (4.16) is selected,

production is controlled by the loading equipment.

Productivity (Lcm/hr) = Truck load (Lcm) * (60 / Load time) (4.18)

Step 9: Efficiency: The productivity calculated with either Eq. (4.17) or (4.18) is

based on a 60 min working hour. That productivity should be adjusted by an

efficiency factor. Longer hauling distances usually result in better driver efficiency.

Driver efficiency increases as haul distances increase out to about 3,000 m, after

which efficiency remains constant [33].

Adjusted productivity (Lcm/hr) = Productivity (Lcm) * (Working

time (min/hr)) / 60 min (4.19)

50

44..33 CCOOSSTT EESSTTIIMMAATTIINNGG

There are two aspects to be considered in judging the appropriateness of a machine

for a particular job. One is its technical applicability, including productive capacity;

and the other is its economic feasibility. In order to select appropriate machines,

machine performance is usually used as a criterion and judged by estimating the

unit costs which are costs spent on handling materials per unit volume. Estimating

costs is a difficult task in earthmoving planning, and in reality construction

organizations use different approaches to classify and calculate costs. This part

discusses cost elements which are significant in methods for calculating

earthmoving equipment costs. These methods are used to estimate costs in the

computer modeling if the user has no readily established hourly costs available

The unit cost of earthmoving works is essentially derived by dividing cost by

production. In its simplest case, if you rented an excavator with operator for $60 per

hour - including all fuel and other costs - and you excavated 100 cubic meters per

hour, your unit cost for excavation would be $0.60 per cubic meter. The hourly cost

of the excavator with operator is called the machine rate. In cases where the

machine and the elements of production are not rented, a calculation of the owning

and operating costs is necessary to derive the machine rate. The objective in

developing a machine rate should be to arrive at a figure that, as nearly as possible,

represents the cost of the work done under the operating conditions encountered and

the accounting system in use. Most manufacturers of machinery supply data for the

cost of owning and operating their equipment that will serve as the basis of machine

rates. However, such data usually need modification to meet specific conditions of

operation, and many owners of equipment will prefer to prepare their own rates

[36].

The machine rate is usually, but not always, divided into fixed costs, operating

costs, and labor costs. For certain cash flow analyses only items which represent a

cash flow are included. Certain fixed costs, including depreciation and sometimes

interest charges, are omitted if they do not represent a cash payment. In this

51

research, all fixed costs discussed below are included. For some analyses, labor

costs are not included in the machine rate. Instead, fixed and operating costs are

calculated. Labor costs are then added separately. This is sometimes done in

situations where the labor associated with the equipment works a different number

of hours from the equipment. In this research, labor is included in the calculation of

the machine rate. Fixed costs are those which can be predetermined as accumulating

with the passage of time, rather than with the rate of work (Figure 4.4). They do not

stop when the work stops and must be spread over the hours of work during the

year. Commonly included in fixed costs are equipment depreciation, interest on

investment, taxes, and storage, and insurance [36].

Figure 4.4 Equipment Cost Model.

Operating costs vary directly with the rate of work (Figure 4.4). These costs include

the costs of fuel, lubricants, tires, equipment maintenance and repairs.

Labor costs are those costs associated with employing labor including direct wages,

food contributions, transport, and social costs, including payments for health and

52

retirement. The cost of supervision may also be spread over the labor costs. The

machine rate is the sum of the fixed plus operating plus labor costs. The division of

costs in these classifications is arbitrary although accounting rules suggest a rigid

classification. The key point is to separate the costs in such a way as to make the

most sense in explaining the cost of operating the men and equipment [36].

44..33..11 FFiixxeedd CCoossttss

Depreciation

The objective of the depreciation charge is to recognize the decline of value of the

machine as it is working at a specific task. This may differ from the accountant's

depreciation schedule-which is chosen to maximize profit through the advantages of

various types of tax laws and follows accounting convention.

Depreciation schedules vary from the simplest approach, which is a straight line

decline in value, to more sophisticated techniques which recognize the changing

rate of value loss over time. The formula for the annual depreciation charge using

the assumption of straight line decline in value is: [36]

D = (P' - S)/N (4.20)

where P' is the initial purchase price less the cost of tires, wire rope, or other parts

which are subjected to the greatest rate of wear and can be easily replaced without

effect upon the general mechanical condition of the machine. S is Salvage value

which defined as the price that equipment can be sold for at the time of its disposal.

N is Economic life which defined as the period over which the equipment can

operate at an acceptable operating cost and productivity. Examples of ownership

periods for some types of road construction equipment, based upon application and

operating conditions, are shown in Table 4.9 [1].

53

Table 4.9 - Selecting ownership period based on operating conditions [1]

ZONE A ZONE B ZONE C

EXCAVATORS Shallow depth utility

construction where

excavator sets pipe and

digs only 3 or 4

hours/shift. Free

flowing, low density

material and little or no

impact. Most scrap

handling arrangements.

Mass excavation or

trenching where

machine digs all the

time in natural bed

clay soils. Some

traveling and steady,

full throttle

operation. Most log

loading applications.

Continuous trenching

or truck loading in rock

or shot rock soils.

Large amount of travel

over rough ground.

Machine continuously

working on rock floor

with constant high load

factor and high impact.

12,000 Hr 10,000 Hr 8,000 Hr

OFF HIGHWAY

TRUCKS &

TRACTORS

Mine and quarry use

with properly matched

loading equipment.

Well maintained haul

roads. Also

construction use under

above conditions.

Varying loading and

haul road conditions.

Typical road-

building use on a

variety of jobs.

Consistently poor haul

road conditions.

Extreme overloading.

Oversized loading

equipment.

25,000 Hr 20,000 Hr 15,000 Hr

Interest

Many owners charge interest as part of hourly owning and operating costs, others

consider it as general overhead in their overall operation. When charged to specific

machines, interest is usually based on the owner‘s average annual investment in the

unit. Interest is considered to be the cost of using capital.

The interest on capital used to purchase a machine must be considered, whether the

machine is purchased outright or financed. If the machine will be used for N years

(where Nis the number of years of use), calculate the average annual investment

during the use period and apply the interest rate and expected annual usage [1]:

Interest Cost = (((P) (N + 1)/(2N))x(interest rate %))/ (hours per

year) (4.21)

54

Sometimes a factor of 0.6 times the delivered – purchase - cost is used as an

approximation of the average annual investment [36].

Taxes and Insurance

Many equipment owners must pay property taxes or some type of usage tax on

equipment. And most private equipment owners will have one or more insurance

policies against damage, fire, and other destructive events. Taxes and insurance, like

interest, can be calculated by either using the estimated tax - insurance rate

multiplied by the actual value of the equipment or by multiplying the tax –

insurance rate by the average annual investment.

44..33..22 OOppeerraattiinngg CCoossttss

Maintenance and Repair

Repair costs are significantly affected by the situation. In any situation, actual cost

experience on similar machines provides the best basis for establishing the hourly

repair cost. Repairs and component lives are normally the largest single item in

operating costs and include all parts and direct labor (except operator‘s wages)

chargeable to the machine. Shop overhead can be absorbed in general overhead or

charged to machines as a percent of direct labor cost, whichever is the owner‘s

normal practice [1].

If experienced owners or cost records are not available, the hourly maintenance and

repair cost can be estimated as a percentage of hourly depreciation (Table 4.10)

[36].

55

Table 4.10Maintenance and repair rates as a percentage of the hourly

depreciation for selected equipment.

Machine Percentage Rate

Crawler tractor 100

Agricultural tractor 100

Rubber-tired skidder with cable chokers 50

Rubber-tired skidder with grapple 60

Loader with cable grapple 30

Loader with hydraulic grapple 50

Power saw 100

Feller-buncher 50

Fuel

The fuel consumption rate for a piece of equipment depends on the engine size, load

factor, the condition of the equipment, operator's habit, environmental conditions,

and the basic design of equipment[36].

To determine the hourly fuel cost, the total fuel cost is divided by the productive

time of the equipment. If fuel consumption records are not available, the following

formula can be used to estimate liters of fuel used per machine hour,

(4.27)

Where LMPH is the liters used per machine hour, K is the kg of fuel used per brake

hp/hour, GHP is the gross engine horsepower at governed engine rpm, LF is the

load factor in percent, and KPL is the weight of fuel in kg/liter. Typical values are

56

given in Table 4.11. The load factor is the ratio of the average horsepower used to

gross horsepower available at the flywheel [36].

Table4.11 Weights, fuel consumption rates, and load factors for diesel and

gasoline engines.

Engine Weight

(KPL)

kg/liter

Fuel Consumption

(K)

kg/brake hp-hour

Load Factor

(LF)

Low Med High

Gasoline 0.72 0.21 0.38 0.54 0.70

Diesel 0.84 0.17 0.38 0.54 0.70

Lubricants

These include engine oil, transmission oil, final drive oil, grease and filters. The

consumption rate varies with the type of equipment, environmental working

condition (temperature), the design of the equipment and the level of maintenance.

In the absence of local data, the lubricant consumption in liters per hour for

skidders, tractors, and front-end loaders could be estimated as [36]

Q= .0006 × GHP (crankcase oil)

Q = .0003 × GHP (transmission oil)

Q = .0002 × GHP (final drives)

Q = .0001 × GHP (hydraulic controls)

These formulas include normal oil changes and no leaks. They should be increased

25 percent when operating in heavy dust, deep mud, or water. In machines with

complex and high pressure hydraulic systems such as forwarders, processors, and

harvesters, the consumption of hydraulic fluids can be much greater. Another rule

of thumb is that lubricants and grease cost 5 to 10 percent of the cost of fuel [36].

57

Tires

Tire costs are an important part of the hourly cost of any wheel machine. Tire costs

are also one of the most difficult to predict with many variables. The best estimate

for tire costs are obtained when tire life estimates are based upon actual customer

experience, and are used with prices the machine owner actually pays for the

replacement tires, if local experience is not available, the following categories for

tire life based upon tire failure mode could be used as guidelines with tire life given

in Table 4.12 [1].

Low/Zone A: almost all tires actually wear through the tread from abrasion.

Medium/Zone B: tires wear out normally but others fail prematurely due to

rock cuts, impacts and non-repairable punctures.

High/Zone C: few, if any, tires wear through the tread due to non-repairable

damages, usually from rock cuts, impacts and continuous overloading.

NOTE: Tire life can often be increased by using extra tread and extra deep tread

tires.

Table 4.12 Guidelines for tire life for off-highway equipment

Equipment Tire Life, hours

Zone A Zone B Zone C

Motor graders 8000 4500 2500

Wheel scrapers 4000 2250 1000

Wheel loaders 4500 2000 750

Skidders 5000 3000 1500

Trucks 5000 3000 1500

58

44..33..33 LLaabboorr CCoossttss

Labor costs include direct and indirect payments such as taxes, insurance payments,

food, housing subsidy, etc. Labor costs need to be carefully considered when

calculating machine rates since the hours the labor works often differs from the

hours the associated equipment works. What is important is that the user define his

convention and then to use it consistently. For example, in felling, the power saw

rarely works more than 4 hours per day, even though the cutter may work 6 or more

hours and may be paid for 8 hours, including travel. If felling production rates are

based upon a six-hour working day, with two hours of travel, the machine rate for

an operator with power saw should consider 4 hours power saw use and eight hours

labor for six hours production [36].

44..44 SSEELLEECCTTIINNGG TTHHEE OOPPTTIIMMUUMM EEQQUUAATTIIOONN TTOO

CCAALLCCUULLAATTEE TTRRUUCCKK SSPPEEEEDD

There are many methods for estimating of productivity, but accurate calculation of

travel speed is essential for determining productivity of earthmoving operations.

Manufacturers‘ performance charts and/or site-collected data are commonly used to

estimate haulers‘ travel time and speed. These charts provide the hauler speed under

positive and negative total resistances without accounting for acceleration and

deceleration zones. These charts are called Rimpull–Speed– Gradeability and Brake

Performance, respectively [1]. Further, charts known as Travel Time charts provide

haulers‘ travel time under loaded and unloaded conditions [1]. To develop a

computer application which could be used for the estimation of productivity we

need to convert this performance chart into an equation. This report is presenting

four methods for estimating haulers' travel speed and presenting the optimum

equation or method to be used for estimating of productivity. For this purpose two

examples have been presented to compare those four methods with traditional

method to select optimum equation (Tables 4.13 and 4.14) – see Appendix A for

calculations detail -.

59

Table 4.13 Summary of example 1

N The Equation Source Result Notes

1

Speed (km/hr) = (273.75 x

Engine HP) / (GMW x Total

resistance)

CATERPILLAR®

PERFORMANCE

HANDBOOK, 2006

[1]

53.91

km/hr

The

Optimum

2 2 39.8066 ( )1000

r r

MR C c V c (Rakha, ASCE) [37]

86.84

km/hr

**

3 3600t

PF

V (Lucic, 2001) [38]

8.50

km/hr

4

375( )( )

( 20( ))H

F

hp ev

W RR S

***

(Gransberg, D. D.,

1996) [39]

54.00

km/hr

The

Optimum

The Traditional method using Truck Performance

Chart from equipment catalogue

53.00

km/hr

** The variations in result may because one of or all the following:

1. This study applied on the 200 lb/hp (100 kg/hp) truck case [38]

2. We was assuming that F = Fmax (tractive force)

*** Note: By examination, it can be seen in situations where a downhill grade (i.e.,

negative grade) is greater than the rolling resistance; the maximum speed is limited

by characteristics of the truck retarder curve or operator braking to remain at safe

speed. In addition, the actual velocity is further restricted by the legal speed limit or

other factors such as the physical geometry of super elevated horizontal curve [39].

so in this case use the top speed at loaded from truck catalogue as a truck speed to

the dump site and use the legal speed limit as a truck speed when it return to the

site.

60

Table 4.14 Summary of example 2

N The Equation Source Result Notes

1

Speed (km/hr) = (273.75 x

Engine HP) / (GMW x Total

resistance)

CATERPILLAR®

PERFORMANCE

HANDBOOK,

2006 [1]

59.90km/hr The

Optimum

2 2 39.8066 ( )1000

r r

MR C c V c (Rakha, ASCE) [37] 86.86km/hr

3 3600t

PF

V (Lucic, 2001) [38] 10.23km/hr

4 375( )( )

( 20( ))H

F

hp ev

W RR S

(Gransberg, D. D.,

1996) [39] 60.10km/hr

The

Optimum

The Traditional method using Truck Performance

Chart from equipment catalogue

56.00

km/hr

Four methods for estimating haulers' travel speed and the optimum equation or

method were presented to be used for estimation of productivity then it was notice

that the optimum method which has been presented in summary table (table 4.13,

4.14) is Equation no. 4 [39]:

375( )( )

( 20( ))H

F

hp ev

W RR S

(4.28)

CCHHAAPPTTEERR FFIIVVEE

DDEECCIISSIIOONN SSUUPPPPOORRTT TTOOOOLL FFOORR EEAARRTTHHMMOOVVIINNGG

PPRROOJJEECCTTSS

62

CCHHAAPPTTEERR 55

DDEECCIISSIIOONN SSUUPPPPOORRTT TTOOOOLL FFOORR

EEAARRTTHHMMOOVVIINNGG PPRROOJJEECCTTSS


This chapter describes the development of the Decision Support Tool for

Earthmoving Projects (DST for EMP) PROEQUIP. It will deal with a detailed

description of the input data set components, basic modeling assumptions made, the

general structure of the computer modeling, simulation program and the database

structure. The input data are one of the most important factors affecting the results

of any modeling and simulation study. In order to calculate and compare production

and cost rates between several different models, a great deal of time could be spent

on the necessary calculations. The computer modeling and simulation system was

designed to facilitate this process. Microsoft Visual Basic.Net was chosen the main

programming language to develop the DST for EMP (PROEQUIP) because it is

powerful and capability. Microsoft Excel was chosen for simulation calculation by

integration with the main system because it is designed to handle tabular data and

because of its popularity. Visual Basic.net was built to work with and extend the

capabilities of MS Office applications, so it does not need the substance of a

programming language used to build full-blown applications from scratch. The

overall aim of this system is to assist managers to manage and estimate the

productivity, duration and cost of earthmoving system. In order to attain above aim,

three specific objectives will have to be achieve:

1) Collection of data needed to compile required databases of:

63

Equipment database: provide truck empty weight, truck payload, truck

horsepower, top loaded speed of the truck and truck heaped capacity

Excavated material database: provide material weight, bucket fill

factor and excavator cycle time based on material type.

Rolling resistance database based on haul road type.

2) Design a mathematical model to assess the performance of a given

earthmoving system to be used for monitoring, control and improvement of

ongoing operations.

3) Design a simulation model assist in decision making to enable the

comparisons among earthmoving systems.

The first section of this chapter covers an overview for Input, output and database.

Starting from the second section will talking about system user interface, system

structure and simulation in detail.

55..22 IINNPPUUTTSS,, OOUUTTPPUUTTSS AANNDD DDAATTAABBAASSEE

The inputs of the PROEQUIP system can be divided into five main groups:

1) Project information inputs group: It optional and it includes inputs that draw

a summary description about the studied project to be used in result report.

2) Job information inputs group: Includes inputs about excavated material type

with a database connection and about job information as efficiency and

working periods.

3) Haul Road inputs group: Include inputs about haul road type which will be

used as a hauler surface from excavating site to dump site. This data is

connecting with a database.

4) Cost inputs group: Include inputs that assist in cost estimating for

earthmoving system

5) Simulation inputs group: Includes inputs regarding to the simulation

calculation. User will first select the number of studied cases as a maximum

64

of five different cases, then selecting the type of equipment which will be

used for every case.

The outputs of the system contain:

1) Deterministic performance results: that assesses the performance of a given

earthmoving system to be used for monitoring, controlling and improving of

ongoing operations. that result gives a direct result for productivity, cost and

duration for an earthmoving system

2) Simulation Result: that assists in decision making to enable the comparisons

among earthmoving systems.

3) Safety Recommendations: that give some safety advises during the job of

earthmoving

The system has been integrated with a Microsoft Access database of soil properties,

road condition and trucks database to facilitate calculation using equation during

programming. The soil properties database, shown in Figure 5.1, contains the table

of available types of earth to be moved (23 types of materials). This database lists

the weight per BCM and per LCM, bucket fill factor and the excavator cycle time

for each type. The sources of soil properties database table are "Caterpillar

Performance Handbook" [1], ―Handbook of Heavy Construction‖ book [7] for

materials properties and ―Construction Planning, Equipment, and Methods" book

[33] for excavator cycle time values. The road conditions database contains a table

which lists the types of haul roads from which the user can choose (21 types of

roads surface). The database also lists the rolling resistances for these road types [1,

7 and 23]. Figure 5.2 illustrates the road conditions database.

The trucks database is the primary database. This database contains a list of trucks.

Each record consists of the model, gross and net powers, empty weight, payload,

top speed at loaded and heaped capacity [1]. There are also a database tables for job

efficiency factors [33].

65

In addition the system contains add new truck button in the user interface from

equipment selection section or in the ―Tool‖ menu. This option facilitates addition

of a new truck into the database. This option uses a user form to add data on all

aspects of the truck. This user form is shown in Figures 5.3. User can also edit,

delete or search for existing truck (Figure 5.4). Figure 5.5 shows flowcharts that

declare the important of every parameter in user interface for results.

Figure 5.1 Soil properties database figure [1, 33]

66

Figure 5.2 Road condition database figure [1, 7, 23]

67

Figure 5.3 Trucks form to add, edit and delete truck

Figure 5.4 Trucks form to search for existing truck

68

Figure 5.5 User interface parameters flowchart

69

55..33 SSYYSSTTEEMM SSTTRRUUCCTTUURREE

55..33..11 SSyysstteemm CCaallccuullaattiioonn

The system performs the estimation calculations as outlined in Chapter 4. The

flowcharts in figure 5.6 and figure 5.7 summarize the calculation steps of the

productivity and unit cost for earthmoving system.

The first step in earthmoving system productivity calculation is to determine the

number of excavator bucket loads it takes to load the truck from equation (4.9). The

actual number of bucket loads placed on the truck should be an integer number. The

second step is to determine the load time that required loading the truck from

equation (4.10). Then it is required to check the truck load volume from equation

(4.11) to compare it with truck heaped capacity then check the truck load weight

from equation (4.12) to compare it with truck payload. Determination of the truck

velocity loaded and empty from haul site to dump site is the next step from equation

(4.28). The sixth step is to determine haul and return time of the truck from equation

(4.13) and (4.14). Dump time will depend on the type of hauling unit and

congestion in the dump area; consider that the dumped time has been assumed as 2

minutes. The next step is to calculate the truck cycle time from equation (4.15) to

determine the number of trucks required to keep the loading equipment – excavator

– working at capacity from equation (4.16). The number of trucks must be an

integer number, so if an integer number of trucks lower than the result of equation

(4.16) is chosen then the trucks will control production and productivity equation

will be (4.17), When an integer number of trucks greater than the result of equation

(4.16) is selected then productivity is controlled by the loading equipment and the

equation will be (4.18).

70

Figure 5.6 Production calculation flowchart for earthmoving system

71

Figure 5.7 Unit cost calculation flowchart for earthmoving system

72

Where (For production calculation):

Nb (Nb1, Nb2) = number of excavator buckets

Cht = B = truck heaped capacity (m3)

Cbe = bucket heaped capacity (m3)

ff = bucket fill factor (from database) (from table 3.5)

tl = load time (min.)

tce = excavator cycle time (sec.) (from database) (from table 3.3 and table 4.2)

Vl = load volume (m3)

Wl = load weight (kg)

Ws = Weight of soil (kg/m3) (from database) (from table 4.4)

Pt = truck payload (kg)

Wgt = gross weight of the truck (kg)

Wet = truck empty weight (kg)

hpt = truck engine net power (hp)

RR = rolling resistance (%) (from database) (from table 4.6)

GR = grade resistance (%)

D = distance from haul to dump site (km)

Vhl = truck speed loaded (km/hr)

Vhe = truck speed empty (km/hr)

th = haul time (min.)

tr = return time (min.)

td = dump time (min.)

tct = truck cycle time (min.)

Nt = number of trucks

E = efficiency (from database)

P = Productivity (Lcm / hr)

Where (For unit cost calculation):

D = equipment depreciation per hour

73

P = purchase price of the equipment

S = Salvage value

i = interest rate

I = interest cost per hour

N = economic life of the equipment (from table 4.10)

is = insurance rate

IS = insurance cost per hour

t = taxes rate

T = taxes cost per hour

L = labor cost per hour

Nh = number of helpers

h = helper cost per hour

F = fuel cost per hour

Fl = fuel cost per liter

K = fuel consumption (kg/brake hp-hour) (from table 4.12)

LF = load factor (from table 4.12)

KPL = weight of fuel (kg/liter) (from table 4.12)

Tic = tire cost per hour

Tcc = tire change (replacement) cost

tr = approximate tire life (from table 4.13)

M = maintenance and repair cost per hour

U = lubricant cost per hour

TC = Total unit cost per hour

Dh = number of working hours per day (hours)

Dd = number of working days per week (days)

hp = equipment engine horse power (hp)

74

55..33..22 TThhee SSiimmuullaattiioonn

There are two common methods for estimation of productivity: (1) deterministic

and (2) probabilistic (Simulation) methods. Deterministic analysis was developed

for simple calculation of the productivity of an earthmoving operation based on the

equipment characteristics, equivalent grades, and the haul distance provided by

performance handbooks published by most manufacturers. A deterministic method

primarily focuses on the use of time durations that are fixed or constant values, with

the assumption that any variability in the task duration is assumed to be ignored

[12]. But the deterministic method does not reflect actual conditions, such as

randomness of work duration. This limitation can be overcome by using simulation.

However, a user without a reasonable background in simulation may struggle with

implementation due to the difficulty of modeling.

Simulation studies are well suited for the analysis of earthmoving operations for

many reasons [12]:

1) Projects generally involve some form of resource interactions where certain

equipment must obtain certain resources before proceeding.

2) Task durations are highly empirical and are thus suited for stochastic

modeling.

3) Projects are affected by external processes such as breakdowns and external

traffic.

Simulation can take all of those elements into account and help estimators gain

greater insight into the interactions and productions of earth moving projects [12].

This section deals with a detailed description of the input data set components, basic

modeling assumptions made and the general structure of the simulation program

which has been integrated within PROEQUIP software. This program is a computer

tool for the simulation, analysis and estimation of the earthmoving projects. Output

of the model can be exported to a reporting or estimating module. This output may

be used as a tool for decision support.

75

During simulation process, when a truck enters a road segment, it is randomly

assigned a travel speed based on the speed study data to find a travel time by

equations. The multiple scenarios created through simulation can be analyzed to

give more insight into the risks and mechanisms of the spreadsheet model. Also

excavator cycle time and dump time have been randomly assigned based on time

study data. The configuration of the haulage road change frequently and

maintaining current data is time consuming and impractical if the data are collected

manually. Estimating travel times through a calculation procedure is preferable in

these cases. The simulation program developed in this study is designed with the

objective of studying the effects on productivity by continuously dispatching trucks

in medium-sized project under various conditions but it tested for conditions which

will be covered in study cases section. Although the simulation program is

developed primarily to test the dispatching procedures, several problems related to a

different size project operation can also be solved. Prior to making a large capital

expenditure for loading and haulage equipment, there is an evident need for careful

evaluation of possible combination of excavators and trucks and haul road

configurations in the light of planned production requirements in order to achieve

minimum production cost.

The following basic modeling assumptions are made in the simulation program in

this study.

1. All trucks in any particular project are identical (i.e. their capacity, motor

power, speed, etc are the same).

2. The project haul roads are designed to provide two-way traffic for the trucks.

3. The excavator must complete loading for any particular truck before it starts

loading another truck.

4. Single material type is assumed for the simulation program and all trucks in

the project dump their loads at the same dumping site.

5. All trucks start operation at the parking area near the hauling point at the

start of the shift and park there at the end of each shift.

76

6. During a simulation run, the haulage system is performing without any rest

(i.e. eight hours per shift).

7. Up to five earthmoving systems can be compared during simulation. A

system in this case can be defined as a certain combination of trucks and

excavator.

The input data to be used in the simulation program have been taken from literature

values [1, 7, 27 and 33] that are most commonly used and from site researches. To

understand the input data, Figure 5.8 shows the model network diagram for the

activities considered during the design stage of the system. Normal probability

distribution has been selected for the random variables of the truck loading (times)

at excavators, dumping (times) at dump and the system unit cost (Figure 5.9). But

Beta probability distribution has been selected for the random variables of the truck

traveling (speed) both loaded and empty (Figure 5.10) (Appendix E). The

parameters which had been used for the random variables are arbitrarily assumed

and are given in Table 5.1. The truck and excavator unit cost random range

variables have been selected to be inserted by the software user because the natural

of the unit cost and its changes according to variable conditions. However, any

other distribution can be used for any random variable in the models with small

changes to the programs easily. To facilitate the sequence logic which has been

used in the simulation, show the pseudocode that included in Figure 5.11.

Table 5.1 Parameters for the Random Variables Used in the Models

Random

Variables

Min.

Value

Max.

value mean

standard

deviation

Type of

distribution Notes

Excavator cycle

time (Sec.) 10 40 25 9.49 Normal

Truck speed loaded

(km/hr) 10

By

user auto

Beta Alpha = 3

Beta = 1 Truck speed empty

(km/hr) 20

By

user Beta

Dump time (min.) 0.30 2.50 1.40 0.68 Normal

Unit cost By user auto Normal

77

Microsoft Excel was chosen as a simulation program calculation because it is

designed to handle tabular data. Also "Crystal Ball" – Excel add-in – has been used

as Excel assistant because it can simulate unlimited number of trials without

increasing the Excel sheet size and without any effect on the software memory. But

the user input data have been integrated with PROEQUIP software.

Figure 5.8 Simulation model network diagram for the activities

Figure 5.9 Normal probability distribution for the random variables

Figure 5.10 Beta probability distribution for the random variables

78

Figure 5.11 - The simulation model pseudocode

79

55..44 UUSSEERR IINNTTEERRFFAACCEE

The User Interface, shown in Figures (5.12, 5.13, 5.14, 5.15, 5.16, 5.17 and 5.18), is

a window designed to accept input from the user. The input boxes which request

user to insert numbers protected to prevent inserting texts. Drop-down menus that

connected to the database are included in order to facilitate data entry. The User

Interface is displays seven windows presented in Tables (5.2, 5.3, 5.4, 5.5, 5.6 and

5.7).

Figure 5.12 User interface – Project information

Table 5.2 User Interface – Window 1 description

Type of data Description

Project in study

(Figure 5.12)

The user may insert the data about studied project. It contains

input requirements that assist in Productivity and cost results

report such as Project name and description. ―Project starting

date‖ box assist in duration and expected finish date

calculation. The system accepts entries in Metric unit only.

There is a link to ―Units Converter‖ program which has been

integrated with the system to facilitate the conversion from

English to Metric.

80

Figure 5.13 User interface – Job information



Job information

(Figure 5.13)

The user may insert the data about excavation job. It contains

excavated material type which was connecting to the database

that using to define the material weight per cubic meter and

bucket fill factor for productivity calculating. There is a box for

excavated material quantity which its value will be used in

project duration and expected finish date calculation. Job and

operator efficiency drop-down menu were connecting to

database to be used in productivity calculating. There are also

―Number of working hours per day‖ and ―Number of working

days per week‖ boxes which will be used in project duration

and expected finish date calculation.

81

Figure 5.14 User interface – Haul road information



Haul Road Data

(Figure 5.14)

It requires the user to input data pertaining to the haul road. The

system allows for division of the haul road into a maximum of

five sections. User must select the road surface type for every

road section, this type was connecting to database in order to

give the rolling resistance of the road (see table 4.6). The user

is prompted to input the distance of each segment, input the

legal speed limit, and input the grade resistance of that

segment. This section is using to calculate truck speed by

rolling resistance and grade resistance as known.

82

Figure 5.15 User interface – Equipment selection section



Equipment

Selecting (Figure

5.15)

It contains a link to database that user may choose a single

model from a list of all available trucks. Also user may need to

insert heaped bucket capacity of excavator and excavator cycle

time. There is an option to make the system select the

opportune cycle time for excavator as a factor of material type

from ―Job information section‖. The gross engine horsepower

is required in cost calculation.

83

Figure 5.16 User interface – Equipment Unit Cost section

Figure 5.17 User interface – Equipment Cost section

84

Table 5.6 User Interface – Windows 5 and 6 description


Equipment Cost

(Figure 5.16 and

5.17)

It allows entry of cost parameters for the project. It is required

to insert cost parameters regarding to the selection. When user

select ―Rental‖ he needs to inserting one value for ―Equipment

Cost per hour‖ this one value includes rental machine cost per

hour plus labors cost per hour (presented in detail in chapter 4).

Figure 5.18 User interface – Simulation section



The Simulation

(Figure 5.18)

It contains a link to database that the user may choose a model

per case of all available trucks for simulation calculating and up

to five cases. Other parameters may be required are haul road

distance and legal speed limit. The rolling and grade resistances

of haul road not important in simulation calculation because the

speed of truck loaded/empty will be generated randomly.

85

55..55 TTHHEE RREESSUULLTTSS

The results section contains three parts of results: find the deterministic

performance results (first module), simulation results (second module) and

recommendations page. The results of the first part- by clicking on the ―RESULTS‖

button – show: the production by LCM/hr, BCM/hr, LCY/hr, BCY/hr, cost per

hour, cost per LCM … etc, number of buckets, number of trucks need to result the

maximum production, maximum truck speed loaded and empty (starting speed) at

haul travel and (end speed) at return travel, project duration per hour and per day

and expected finish date. This section is shown in Figure 5.19. The accuracy of the

results depends on the accuracy of the user data entry. For example if the user

inserted the total quantity of the excavation material equal to zero the results of the

duration of the project will be not accurate.

Figure 5.19 The production and cost results page

There is a link from result page to the calculation data sheet. This data sheet (Figure

5.20) assists the user to print a calculation report, to edit results and add his notes on

this report. This data sheet has been designed using Microsoft Excel to give the user

the ability to customize the report. All data will be added automatically regarding to

86

user‘s data entries in ―user interface‖ page but data are not protected so user can

save, print and edit the results data.

Figure 5.20 The results data sheet page

87

The results of the simulation section (module 2) of the software have been

calculated using ―Microsoft Excel‖. The simulation models collect the inputs from

the user interface in PROEQUIP software then make the calculation regarding to

this inputs. Because the random variables may change every trip during the job, all

simulation trials just simulate project job until it finished for one time, Those trials

have been repeated x times - as user selection - using CRYSTAL BALL software.

Also the productivity, unit cost and duration have been stored to use in histogram

using PROEQUIP. The user can select the proper number of trials according to the

required accuracy of the results (Figure 5.21, Figure 5.22 and Figure 5.23). The

trips trials has been designed for 1,000 m3 excavation quantities jobs, but the results

will be fit for more than 1,000 m3 quantities jobs (Figure 5.11).

The results section in the simulation can be divided into four parts:

1) This Part shown in Figure 5.24 presents the summary of the simulation

calculations which show the average, standard deviation, maximum value

and minimum value of unit cost of the selected equipment and conditions per

hour for all probability of buckets numbers, it also presents the frequency of

the job unit cost values.

2) This Part shown in Figure 5.25 presents the summary of the simulation

calculations which show the average, standard deviation, maximum value

and minimum value of production of the selected equipment and conditions

in LCM per hour for all probability of buckets numbers, it also presents the

frequency of the job production values.

3) This Part presents the summary of the simulation calculations which show

the average, standard deviation, maximum value and minimum value of the

job duration in hours for all probability of buckets numbers, it also presents

the frequency of the job duration values.

4) This Part shown in Figure 5.26 which presents the overlay charts to assist in

comparison and decision making of earthmoving systems productivity and

cost.

88

Figure 5.21-The simulation calculations interface – trials section A

Figure 5.22-The simulation calculations interface – trials section B

Figure 5.23-The simulation calculations interface – trials section C

89

Figure 5.24 The simulation results – unit cost

Figure 5.25 The simulation results – Production

90

Figure 5.26 The Overlay charts for productivity and cost

91

The page of recommendations (advices) shown in Figure 5.27 and 5.28 contains

important safety recommendations divided into one safety manual and 16 safety

videos.

Figure 5.27 The recommendations (advices) page

Figure 5.28 safety video sample in the recommendations (advices) page

92

55..66 EEXXAAMMPPLLEESS FFOORR TTRRAADDIITTIIOONNAALL CCAALLCCUULLAATTIIOONN

UUSSIINNGG PPRROOEEQQUUIIPP ((PPRROOEEQQUUIIPP VVEERRIIFFIICCAATTIIOONN))

In this section, example problems are presented. The estimation calculations have

been performed by hand and run through the system in order to validate the first

module of PROEQUIP which is deterministic in nature.

55..66..11 EExxaammppllee 11

Given: its Caterpillar 725 Articulated Truck:

1. Truck Gross power = 309hp

2. Truck Net power = 301hp

3. Truck Net empty weight = 22,260 kg

4. Truck Payload = 23,590 kg

5. Truck Top speed loaded = 56.8 km/hr

6. Truck heaped capacity = 14.4 m3

7. Excavator heaped capacity = 1.9 m3

8. Quantity of excavation material = 20000 m3

9. Project working hours per day = 8 hr

10. Project working days per week = 6 days

11. Haul road type = smooth roadway (rolling resistance = 1.5%) (Table 4.5)

12. Haul material type = dry clay (loose material weight = 1480 kg/m3, bucket

fill factor = 90%, excavator cycle time = 23 seconds and load factor = 0.81)

(Table 4.4)

13. The haul road from the borrow site to the dump is 4 km uphill grade of 2%

14. Job efficiency = 50 minutes per hour = 0.83

15. Operators are good = 0.95

16. Excavator engine power = 115 hp

17. Road legal speed = 90 km/hr

93

Cost data:

1. Truck purchase price = 850,000 LE

2. Truck Salvage price = 200,000 LE

3. Excavator purchase price = 450,000 LE

4. Excavator salvage price = 90,000 LE

5. Interest rate = 5%

6. Taxes rate = 9%

7. Insurance rate = 6%

8. Operator cost = 6 LE/hr

9. Helper cost = 4 LE/hr

10. There are 3 helpers

11. Cost of fuel per liter = 1 LE

12. Truck tire cost = 1000

13. Engine type is diesel

14. Site condition: shallow depth excavation, high safety and good management

at site (ownership period = 25,000 hrs for truck & 12,000 hrs for excavator

(ZONE A))

Required: Estimate the earthmoving productivity and earthmoving unit cost per

hour

Figure 5.29 Caterpillar 725 Articulated Truck specifications

94

Example of manual solution:

Step1:

Balanced number of buckets = 14.4 / (1.9 x 0.9) = 8.42

The actual number of buckets must be an integer numbers we have 8 or 9 buckets

Step 2: Load time

8 buckets 9 buckets

Load time = 8 x 23 / 60 = 3.067 min

Load volume = 8 x 1.9 x 0.9 = 13.68 m3

< 14.4 m3 OK

Load weight = 13.68 x 1480 = 20,246.4 kg

< payload OK

Load time = 9 x 23 / 60 = 3.45 min

Load volume = 9 x 1.9 x 0.9 = 15.39 m3

> 14.4 m3 use 14.4 m3

Load weight = 14.4 x 1480 = 21,312 kg

< payload OK

Step 3: Haul time

RR = 1.5% = 1.5 x 20 lb/ton = 30 lb/ton, GR = +2% = 2 x 20 lb/ton = +40 lb/ton

Engine horsepower = 301 hp, Truck empty weight = 22,260 kg, TR = 70 lb/ton

8 buckets 9 buckets

Weight fully loaded = 22260 + 20246.4 =

42,506.4 / 909.09 =

46.757 lton

Speed = ((375 x 301)/(46.757 (70))) x 1.61

= 55.52 km/hr

Haul time = (4 x 60) / 55.52 = 4.3227 min

Weight fully loaded = 22260 + 21312 =

43,572 / 909.09 =

47.929 lton

Speed = ((375 x 301)/(47.929 (70))) x 1.61

= 54.166 km/hr

Haul time = (4 x 60) / 54.166 = 4.4308 min

95

Step 4: Return time:

RR = 1.5% = 1.5 x 20 lb/ton = 30 lb/ton, GR = -2% = 2 x 20 lb/ton = -40 lb/ton

Engine horsepower = 301 hp, Truck empty weight = 22,260/909.09 = 24.486 lton

TR = -10 lb/ton

Speed = ((375 x 301)/(24.486 (-10))) x 1.61

The speed will be in –ve so use max. road legal speed = 90 km/hr

Return time = (4 x 60) / 90 = 2.667 min

Step 5: Dump time = 2 min

Step 6: Truck cycle time:

8 buckets 9 buckets

Load time (min.) 3.067 3.45

Haul time (min.) 4.3227 4.4308

Dump time (min.) 2 2

Return time (min.) 2.667 2.667

Truck cycle time (min.) 12.0558 12.5476

Step 7: Number of trucks:

8 buckets 9 buckets

No. of trucks = 12.0567 / 3.06 = 3.931 No. of trucks = 12.5478 / 3.45 = 3.63704

96

Step 8: Production:

8 buckets 9 buckets

3 trucks 4 trucks 3 trucks 4 trucks

Load volume x no. of

trucks x 60 / truck cycle

time

Load volume x 60 / load

time



time


time

204.235 LCM/hr 267.62 LCM/hr 206.57 LCM/hr 250.43 LCM/hr

Choose maximum production = 267.62 LCM/hr

Actual production = 267.62 x 0.83 x 0.95 = 211.02 LCM/hr

At:

- Number of trucks = 4 trucks

- Number of buckets per truck = 8 buckets

- Haul speed (1st road segment) = 55.52 km/hr

- Return speed (last road segment) = 90 km/hr

Cost calculation:

Hourly Owning and Operating Cost Estimation

a) Truck depreciation = no. of trucks (purchase price – salvage price) /

ownership period = 4 (850,000 – 200,000) / 25,000 = 104 LE/hr

b) Excavator depreciation = no. of hoes (purchase price – salvage price) /

ownership period = (450,000 – 90,000) / 12,000 = 30 LE/hr

c) Truck interest cost = no. of equipment (purchase price x ((N+1)/2N) x

interest rate) / (52 x working hrs per day x working days per week) = 4

((850,000 x 0.6 x 0.05) / (52 x 8 x 6)) = 40.86 LE/hr

97

d) Truck insurance cost = no. of equipment (purchase price x ((N+1)/2N) x


((850,000 x 0.6 x 0.06) / (52 x 8 x 6)) = 49.04 LE/hr

e) Truck taxes cost = no. of equipment (purchase price x ((N+1)/2N) x interest

rate) / (52 x working hrs per day x working days per week) = 4 ((850,000 x

0.6 x 0.09) / (52 x 8 x 6)) = 73.56 LE/hr

f) Excavator interest cost = no. of equipment (purchase price x ((N+1)/2N) x


((450,000 x 0.6 x 0.05) / (52 x 8 x 6)) = 5.4 LE/hr

g) Excavator insurance cost = no. of equipment (purchase price x ((N+1)/2N) x


((450,000 x 0.6 x 0.06) / (52 x 8 x 6)) = 6.5 LE/hr

h) Excavator taxes cost = no. of equipment (purchase price x ((N+1)/2N) x


((450,000 x 0.6 x 0.09) / (52 x 8 x 6)) = 9.7 LE/hr

i) Operators cost = 5 x 6 = 30 LE/hr

j) Helper cost = 3 x 4 = 12 LE/hr

k) Fuel cost for truck = 4 x 309 x 0.17 x 0.54 x 1 / 0.84 = 135.08 LE/hr

l) Fuel cost for excavator = 115 x 0.17 x 0.54 x 1 / 0.84 = 12.57 LE/hr

m) Truck repair cost = depreciation = 104 LE/hr

n) Excavator repair cost = depreciation = 30 LE/hr

o) Lubricants cost for truck = 0.1 x 135.08 = 13.508 LE/hr

p) Lubricants cost for excavator = 0.1 x 12.57 = 1.257 LE/hr

q) Truck additional cost = 4 x 5 = 20 LE/hr

r) Excavator additional cost = 5 LE/hr

s) Truck tire replacement cost = 4 x (1.2 x (1000/5000)) = 0.96 LE/hr

t) Total cost = 104 + 30 + 40.86 + 49.04 + 73.56 + 5.4 + 6.5 + 9.7 + 30 + 12 +

135.08 + 12.57+ 104 + 30 + 13.508 + 1.257 + 20 + 5 + 0.96 = 683.44

LE/hr

98

Example solution by PROEQUIP software (first module):

The output of the PROEQUIP software is shown in Figures 5.30 and table 5.8.

Table 5.8 The results of example 1 using PROEQUIP software

Parameters Values

Actual Production (LCM/hr) 211.044

Truck speed loaded (km/hr) 55.52

Truck speed empty (km/hr) 90

No. of required trucks 4

No. of buckets per truck 8

Earthmoving system unit cost (LE/hr) 683.47

Figure 5.30 The results of example 1 in the Results page

99

55..66..22 EExxaammppllee 22

Given: its Caterpillar 772 Articulated Truck:

1. Truck Net power = 535hp

2. Truck Net empty weight = 35,454 kg

3. Truck Payload = 45,000 kg

4. Truck Top speed loaded = 79.7 km/hr

5. Truck heaped capacity = 31.3 m3

6. Excavator heaped capacity = 2.8 m3

7. Quantity of excavation material = 50000 m3

8. Project working 8 hours per day and 6 days per week

9. Haul road type:1 Km smooth roadway 1% grade (rolling resistance (RR) =

1.5%) + 2 Km dirt roadway 1% grade (RR = 4%) + 2 Km sand -4% grade

(RR = 10%) (Table 4.5) with 90 Km/hr legal speed

10. Haul material type = dry gravel (loose material weight = 1690 kg/m3, bucket

fill factor = 95%, excavator cycle time = 23 seconds and load factor = 0.89)

(Table 4.4)

11. Job efficiency = 50 minutes per hour = 0.83

12. Operators are good = 0.95

Cost data: Excavator rental cost =150 LE/hr and truck rental cost = 200 LE/hr

Required: Estimate the earthmoving productivity and earthmoving unit cost/ hour

Figure 5.31-Caterpillar 725 Articulated Truck specifications

100

Example of manual solution:

Step1:

Balanced number of buckets = 31.3 / (2.8 x 0.95) = 11.77

The actual number of buckets must be an integer numbers we have 8 or 9 buckets

Step 2: Load time

11 buckets 12 buckets

Load time = 11 x 23 / 60 = 4.217 min

Load volume = 11 x 2.8 x 0.95 = 29.26 m3

<31.3 m3 OK

Load weight = 29.26 x 1690 = 49,449.4 kg

>payload NOT OK

Use 10 buckets

Load time = 10 x 23 / 60 = 3.83 min

Load volume = 10 x 2.8 x 0.95 = 26.6 m3< 31.3 m3 OK

Load weight = 26.6 x 1690 = 44,954 kg <payload OK

Step 3: Haul time

10 buckets

Road 1: RR = 1.5% = 1.5 x 20 lb/ton = 30 lb/ton, GR = +1% = 1 x 20 lb/ton = +20 lb/ton

Engine horsepower = 535hp, TR = 50 lb/ton

Weight fully loaded = (35454 + 44954) / 909.09 = 88.45lton

Speed = ((375 x 535)/(88.45 (50))) x 1.61= 73.037 km/hr

Haul time = (1 x 60) / 73.037 = 0.82 min

Road 2: RR = 4% = 4 x 20 lb/ton = 80 lb/ton, GR = +1% = 1 x 20 lb/ton = +20 lb/ton


101

Weight fully loaded = (35454 + 44954) / 909.09 = 88.45 lton

Speed = ((375 x 535) / (88.45 (100))) x 1.61 = 36.52 km/hr

Haul time = (2 x 60) / 36.52 = 3.286 min

Road 3: RR = 10% = 10 x 20 lb/ton = 200 lb/ton, GR = -4% = -4 x 20 lb/ton = -80 lb/ton


Weight fully loaded = (35454 + 44954) / 909.09 = 88.45 lton

Speed = ((375 x 535) / (88.45 (120))) x 1.61 = 30.43 km/hr

Haul time = (2 x 60) / 30.43 = 3.943 min

Total haul time = 0.82 + 3.286 + 3.943 = 8.049 min.

Step 4: Return time:

Road 3: RR = 1.5% = 1.5 x 20 lb/ton = 30 lb/ton, GR = -1% = -1 x 20 lb/ton = -20 lb/ton


Weight empty = (35454) / 909.09 = 39 lton

Speed = ((375 x 535) / (39 (10))) x 1.61 -ve speed use 90 km/hr

Return time = (1 x 60) / 90 = 0.67 min

Road 2: RR = 4% = 4 x 20 lb/ton = 80 lb/ton, GR = -1% = -1 x 20 lb/ton = -20 lb/ton



Speed = ((375 x 535) / (39 (60))) x 1.61 > legal speed use 90 km/hr

Return time = (2 x 60) / 90 = 1.33 min

Road 1: RR = 10% = 10 x 20 lb/ton = 200 lb/ton, GR = +4% = 4 x 20 lb/ton = 80 lb/ton

Engine horsepower = 535hp, TR = 280lb/ton


Speed = ((375 x 535) / (39 (280))) x 1.61 = 29.58 km/hr

Return time = (2 x 60) / 29.58 = 4.057 min

Total return time = 0.67 + 1.33 + 4.057 = 6.057 min

Step 5: Dump time = 2 min

102

Step 6: Truck cycle time:

10 buckets

Load time (min.) 3.83

Haul time (min.) 8.049

Dump time (min.) 2

Return time (min.) 6.057

Truck cycle time (min.) 19.936

Step 7: Number of trucks:

10 buckets

No. of trucks = 19.936 / 3.83 = 5.2

Step 8: Production:

10 buckets

5 trucks 6 trucks



time


time

400.28 LCM/hr 416.71 LCM/hr

Choose maximum production = 416.71 LCM/hr

Actual production = 416.71 x 0.83 x 0.95 = 328.57 LCM/hr At:

- Number of trucks = 6 trucks

- Number of buckets per truck = 10 buckets

- Haul speed (1st road segment) = 73.037 km/hr

- Return speed (last road segment) = 90 km/hr

103

Cost calculation:

Truck cost = 6 x 200 = 1,200 LE/hr, Excavator cost = 150 LE/hr

Total earthmoving unit cost = 1,350 LE/hr

Example solution by PROEQUIP software (first module):

The output of the PROEQUIP software is shown in Figures 5.32 and table 5.9.

Table 5.9 The results of example 2 using PROEQUIP software

Parameters Values

Actual Production (LCM/hr) 328.290

Truck speed loaded (km/hr) 73.04

Truck speed empty (km/hr) 90

No. of required trucks 6

No. of buckets per truck 10

Earthmoving system unit cost (LE/hr) 1350

Figure 5.32 The results of example 2 in the Results page

104

55..77 TTHHEE SSIIMMUULLAATTIIOONN RREESSUULLTTSS AACCCCUURRAACCYY::

The discussing of the accuracy of the simulation results by an example will be

presenting in this section of research. The PROEQUIP user can select the accuracy

of the job results by selecting the number of trials at the simulation inputs interface

(Figure 5.18). Table 5.10 presents the comparison of the production results between

1000 and 10000 number of trials using the inputs data from example 1 in last

section (725 Articulated Truck)

Table 5.10 The production results according to number of trials change

No. of trials The results

1000

10000

105

55..88 AAPPPPLLIICCAATTIIOONN OOFF PPRROOEEQQUUIIPP OONN RREEAALL CCAASSEESS::

In order to show how PROEQUIP may be used in real projects, two actual projects

were simulated using module 2 in PROEQUIP.

55..88..11 CCaassee ssttuuddyy 11:: GAZADCO Project (Table 5.11)

Project Name: GAZADCO SHRIMP FARM EXPANSION (Phase II)

Project description: The site of this work is located within the 500 hectares area of

Gazan Agricultural Development Company (GAZADCO) in Al-Sawarmah (Figure

5.33), approximately 50 kilometers south of the City of Gizan, along the coast of the

Red Sea (Figures 5.34, 5.35, 5.36, 5.37 and 5.38). The site is accessible from Gizan

through a concrete-paved highway, which passes about 450 meters at the nearest

point of the boundary of the area. From the asphalt-paved highway, the site is

connected by a gravel-surfaced road leading to the different areas within the project

site. (Project state: in progress)

Table 5.11GAZADCO Project data and description

Project location: Gizan, Kingdom of Saudi Arabia

Company name:

Project BOQ Price: 28,738,667 Saudi Riyals (SR)

Excavation material type: Wet clay

Project Area: 910,000 m2

Area of the study part of the

project: (Figure 5.33) 75,000 m

2

Quantity of excavation for project: 1,816,331 m3

Quantity of excavation for the

study part of the project: (Figure

5.33)

150,000 m3

Distance from site to dump: 9000 m

Number of simulation trials: 5000 trials

106

Figure 5.33 –GAZADCO project (site plan)

107

Figure 5.34 –GAZADCO project (shrimp pond works)

Figure 5.35 –GAZADCO project (Earthmoving works)

108

Figure 5.36 –GAZADCO project (Excavation works A)

Figure 5.37 –GAZADCO project (Excavation works B)

109

Figure 5.38 – GAZADCO project (Excavation works C)

The available equipment - which owned by the company or that available in site

area – have been collected and listed in Tables 5.12, 5.13, 5.14 and 5.15 and in

Figures 5.39, 5.40, 5.41, 5.42, 5.43, 5.44, 5.45, 5.46, 5.47, 5.48 and 5.49 to be used

during the cases or scenarios selection.

Table 5.12 GAZADCO Project Company Equipment (Trucks)

S.N Type (Model) Payload

(ton)

Heaped

capacity

(m3)

Number

available

Equipment cost

(SR)

T1 Mercedes Benz 3328K

(1987) – Figure 5.39 18.5 16 8

P = 419,000

S = 65,000

(62.58 +- 10% SR/hr)

T2 Mercedes Benz 2638

(1993) – Figure 5.40 19 13 6

P = 280,000

S = 50,000

(50.20 +- 10% SR/hr)

T3 Mercedes Benz 2635

(1991) – Figure 5.41 20 14 8

P = 297,000

S = 50,000

(51.89 +- 10% SR/hr)

T4 Volvo – FM12.420

(2004) – Figure 5.42 19.2 14 13

P = 507,000

S = 45,000

(73.37 +- 10% SR/hr)

T5 Mercedes Benz

2628(1983) – Figure 5.43 18.96 15 14

P = 318,000

S = 45,000

(54.57 +- 10% SR/hr)

110

Table 5.13 GAZADCO Project Company Equipment (Excavators)

S.N Type (Model)

Heaped

capacity

(m3)

Number

available Equipment cost (SR)

E1 Hyundai R140 LC – 7 – Figure

5.44 1.5 1

P = 310,000

S = 90,000

(96.46 +- 10% SR/hr)

E2 Caterpillar 325 DL – Figure 5.45 1.9 1

P = 390,000

S = 100,000

(110.40 +- 10% SR/hr)

Where:

P = Equipment purchase price, S = Equipment Salvage value, Operator cost = 10

SR/hour, Helper cost = 6 SR/hour, Number of helpers = 4 helpers, Truck tire cost =

1,000 SR and Fuel cost = 0.25 SR/liter (Diesel)

Table 5.14 GAZADCO Project Equipment available for renting (Trucks)


(ton)

Heaped

capacity

(m3)

Number

available

Equipment unit

cost (SR/day)

RT1 Mercedes Benz 4143

(2003) – Figure 5.46 19 13 8 600 - 680

RT2 Mercedes Benz 4037

(1997) – Figure 5.47 19 12 4 560 - 620

Table 5.15 GAZADCO Project Equipment available for renting (Excavators)

S.N Type (Model)

Heaped

capacity

(m3)

Number

available

Equipment unit

cost (SR/day)

RE1 Kumatsu PC240 LC – Figure 5.48 1.5 1 680

RE2 Caterpillar 225 – Figure 5.49 1.3 1 680

111

Figure 5.39 –GAZADCO project -

Mercedes Benz 3328K (1987)


Mercedes Benz 2638 (1993)




Volvo – FM12.420 (2004)


Mercedes Benz 2628(1983)


Hyundai R140 LC – 7

112


Caterpillar 325 DL






Kumatsu PC240 LC

Figure 5.49 –GAZADCO project - Caterpillar 225

Scenarios assumed in the study:

Scenario 1 (Case 1) (actual scenario): E1 + T1 (up to 8 trucks)

Scenario 2 (Case 2): E2 + T2 (up to 6 trucks)



Scenario 5 (Case 5): E1 + RT2 (up to 4 trucks)

Simulation results for all Scenarios: Overlay charts for all cases (Figure 5.50)

113

After running the simulation using PROEQUIP, the results will be present into three

different types of outputs. The first output type which shown in Figure 5.50 assist

user to identify the productivity or unit cost for specific case. The second output

type presented in Figure 5.51 is an overlay output chart which assists the user to

compare between all cases of studying and select the appropriate case according to

user point of view. The final type of output suggests the optimum case that can be

used by arranging the cases as shown in Figure 5.52.

Figure 5.50 – The productivity distribution for the first case

114

PROEQUIP simulation outputs – based on selected cases of study:

Figure 5.51 –The simulation overlay charts for all study cases

115

From the previous overlay charts of the productivity and cost (Figure 5.51) the

optimum selection that gives maximum production is case 4 (Scenario4):

(Caterpillar 325 DL ) work with (Mercedes Benz 2628) trucks

The optimum selection that gives minimum total cost is case 4 (Scenario 4):

(Caterpillar 325 DL ) work with (Mercedes Benz 2628) trucks

Figure 5.52 –The suggesting optimum cases to be selected

116

To validate the output, user should compare the actual work on site to the

PROEQUIP results that can be achieved using PROEQUIP deterministic

performance result and the data from the first case. While project in progress and by

using the same equipment in this case in another location in the site, the system

finish 9400 m3 in 14 days (9400/4/10 hrs per day) = 235 Lm

3/hr using excavating

cycle time = 22 second. But using PROEQUIP deterministic performance result the

productivity must to be equal to 257.727 Lm3/hr and using the simulation as shown

in Figure 5.50 the average productivity may equal to 240 Lm3/hr. From the previous

results the manager should be aware to improve project productivity by using

PROEQUIP because the actual productivity was at the 28th

percentile of the results.

117

55..88..22 CCaassee ssttuuddyy 22:: Kabary-Matrooh Project (Table 5.16)

Project Name: Increase Kabary-Matrooh railway efficiency

Project description: Increase Kabary-Matrooh railway efficiency, construct new

stations, repair existing stations, and construct new rests and buildings from 15km

region to 43km region (Figure 5.53). The project owner is "The Nationalistic

Authority of Egypt Railway – Construction Engineering Department". (Project

state: finished in year 2000)

Table 5.16 Kabary-Matrooh Project data and description

Project location: MarsaMatrooh - Egypt

Company name:

GENERAL NILE COMPANY FOR

ROAD CONSTRUCTION

Project BOQ Price: LE 9,599,279

Excavation material type: Sand

Project Length: 28 km'

Length of the study part of the

project 5 km'

Quantity of excavation for project: 25000 m3

Quantity of excavation for the

study part of the project 4000 m

3

Distance from site to dump: 4000 m

Number of simulation trials: 5000 trials

118

Figure 5.53 – NILE COMPANY project (site works)

The available equipment - which owned by the company or that available in site

area – have been collected and listed in Tables 5.17 and 5.18 and in Figures 5.54,

5.55, 5.56 and 5.57 to be used during the cases or scenarios selection.

Table 5.17 Kabary-Matrooh Project Company Equipment (Trucks)


(ton)

Heaped

capacity

(m3)

Number

available

Equipment cost

(EGP)

T1 Mercedes Benz 3331 –

Figure 5.53 19 12 11

P = 520,000

S = 100,000

(98.80 +- 10% EGP/hr)

T2 Scania 113H – Figure

5.54 14 10 5

P = 400,000

S = 100,000

(84.75 +- 10% EGP/hr)

119

Table 5.18 Kabary-Matrooh Project Equipment for renting (Excavators)

S.N Type (Model)

Heaped

capacity

(m3)

Number

available

Equipment unit cost

(EGP/day)

RE1 Kumatsu PW160-7 wheeled

excavator – Figure 5.55 1.0 1 700

RE2 Kumatsu PC210 LC crawler

excavator – Figure 5.56 1.3 1 800

Where: P = Equipment purchase price, S = Equipment Salvage value, Taxes rate =

15%, Operator cost = 6 EGP/hour, Helper cost = 4 EGP/hour, Number of helpers =

4 helpers, Truck tire cost = 600 EGP, Fuel cost = 0.95 EGP/liter (Diesel)

Figure 5.54 –NILE COMPANY

project - Mercedes Benz 3331

Figure 5.55 –NILE COMPANY

project - Scania 113H

Figure 5.56 – Kumatsu PW160 Figure 5.57 –Kumatsu PC210 LC

120

Scenarios assumed in the study:

Scenario 1 (Case 1) (actual scenario): RE1 + T1 (up to 11 trucks)

Scenario 2 (Case 2): RE2 + T1 (up to 11 trucks)



Simulation results for all Scenarios: Overlay charts for all cases (Figure 5.57)

After running the simulation using PROEQUIP, the results will be present into three

different types of outputs. The first output type which shown in Figure 5.58 assist

user to identify the productivity or unit cost for specific case. The second output

type presented in Figure 5.59 is an overlay output chart which assists the user to

compare between all cases of studying and select the appropriate case according to

user point of view. The final type of output suggests the optimum case that can be

used by arranging the cases as shown in Figure 5.60.

Figure 5.58 – The productivity distribution for the first case

121

PROEQUIP simulation outputs – based on selected cases of study:

Figure 5.59 –The simulation overlay charts for all study cases

122

From the previous overlay charts of the productivity and cost (figure 5.59) the

optimum selection that gives maximum production is case 4 (Scenario 4):

(Kumatsu PC210 LC crawler excavator) excavator work with (Scania 113H)

trucks

The optimum selection that gives minimum total cost is case 2 (Scenario 2):

(Kumatsu PC210 LC crawler excavator) excavator work with (Mercedes

Benz 3331) trucks

Figure 5.60 –The suggesting optimum cases to be selected

123

To validate the output, user should compare the actual work on site to the

PROEQUIP results that can be achieved using PROEQUIP deterministic

performance result and the data from the first case. The project is already finish but

according to the contractor the excavator in this site could excavate around 1370 m3

per day (1370/10 hrs per day) = 137 Lm3/hr using excavating cycle time = 20

second. But using PROEQUIP deterministic performance result the productivity

must to be equal to 153.90 Lm3/hr and using the simulation as shown in Figure 5.50

the average productivity may equal to 144 Lm3/hr. From the previous results the

manager should be aware to improve project productivity by using PROEQUIP

because the actual productivity was at the 7th

percentile of the results.

55..88..33SSeelleeccttiinngg tthhee ooppttiimmuumm ssiimmuullaattiioonn''ss rreessuullttss::

As notice in the above examples, the selection of the optimum solution of the

simulation's results mainly depends on the site management efficiency of the

manager or engineer and his ability to make decisions, however its recommended to

use the previous method at the case study for optimum solution selection and to take

decision about the proper equipment for the job. Figure 5.59 show the alternative

method for equipment selection using PROEQUIP simulation.

The simulation's results may used in another field instead of the equipment selection

field, for example to check the existing job efficiency and site's equipment

productivity or to expect the required duration to complete the job or the project

total cost.

124

Figure 5.61 –The simulation overlay – probability - charts for all study cases

(the upper for first case of study and the rest for second case of study)

CCHHAAPPTTEERR SSIIXX

CCOONNCCLLUUSSIIOONN AANNDD RREECCOOMMMMEENNDDAATTIIOONNSS

126

CCHHAAPPTTEERR 66

CCOONNCCLLUUSSIIOONN AANNDD RREECCOOMMMMEENNDDAATTIIOONNSS

66..11 SSUUMMMMAARRYY AANNDD CCOONNCCLLUUSSIIOONN

A recap of what has been covered should help when placing the contributions into

perspective. The research was organized into four main parts. Figure 6.1 depicts

these four parts as they relate to each other and the chapters of the dissertation.

Figure 6.1-The organization of the research

127

Part I: Understanding the problem

Part I provided the frame of reference and context for the research.In Chapter 1, the

topic and research was introduced. The objectives, scope, limitations, and

methodology were presented. An outline of the dissertation was provided.

Chapter 2 provided valuable background information to aid in the understanding of

earthmoving researches and modeling. Chapter 3 was a detailed discussion of the

Earthmoving operations managing and control.

Part II: Defining the Work

Part II addressed the work to be accomplished by providing further details on the

nature of the data and the analysis definition aspects of this research.

Part III: The Work

This part of the research was where most of what was actually done was described.

The complicated process of preparing the data and design of the system was

covered in Chapter 5.

Part IV: The Benefits

The final part of the research focused on the uses and contributions of the work

performed.

The advantage of PROEQUIP tool can be summarized into five points:

1) This tool can assist manager in selecting the optimum system during the

work by presenting up to four figures of results

2) Using PROEQUIP deterministic performance result, manager can monitor

and control the project.

3) Using PROEQUIP deterministic performance result or simulation result,

manager can expect the finish time of the work or of the total project.

4) Using PROEQUIP deterministic performance result or simulation result,

manager can expect the project total cost.

128

5) This tool can assist manager to plan and arrange the project work by

selecting the appropriate case for every area in the site.

Using this model, equipment managers will be able to produce better estimates of

average productivity and unit costs for their fleets of equipment. Better estimates

can translate into less uncertainty about profit for the company under the

competitive bidding process. This application can help the equipment manager

maintain an optimum fleet of equipment. It can help an equipment manager make

decisions concerning acquisitions, maintenance, repairs, rebuilds, replacements, and

retirements.

Finally PROEQUIP can be defined as it is an aid tool for selecting earthmoving

equipment based on its productivity only or its unit cost only or based on

productivity and unit cost together.

66..22 RREECCOOMMMMEENNDDAATTIIOONNSS FFOORR FFUUTTUURREE RREESSEEAARRCCHHEE

Throughout the course of this research, a number of areas were identified that could

provide fruitful results if investigated further. While it is hoped that this system

would prove to be immediately useful to an estimator working on an earthmoving

project, there are some ideas to use or program applications that can be worked

together with PROEQUIP system to expand or otherwise improve it. For example,

increase the database lists of the Soil Properties and Road Conditions contain

additional lists of different types of roads and soils, along with their applicable

properties or increase haul road sectors or adding a database for excavators.

Simulation can be improved also by adding integrating animations describe the

simulation results or adding a haul road sectors - for example -.

The simulation model developed in this study can be modified also to consider the

case of variable number of operating excavators to prompt the users for entering the

number of excavators as an input parameter. Also, the simulation experiments can

be extended to include a wider range of operating number of trucks to determine the

129

optimum conditions based on numerical results or to make an EXCEL extension

that select the optimum system based on simulation histograms. The simulation

model developed should be validated in an existing real project.

The limitations and assumptions which had been presented in first and fifth chapters

can be using in future works. For example researchers can use different type of

material in the same project or use more than one type of truck per case.

Finally, while the source code of the software has been attached in appendix with

research, the system might be expanded to include different types of earthmoving

equipment. For example, databases of backhoes and trucks could be added. The

User Interface could then be changed to allow the user to specify more than one

type of equipment to be compared with others.

130

RREEFFEERREENNCCEESS

[1] Caterpillar. "Caterpillar Performance Handbook", ed. 36th. Caterpillar

Tractor Company manual, Peoria, Illinois, USA, 2006.

[2] Griffis, F.H. Jr. "Optimizing Haul Fleet Size Using Queuing Theory", ASCE,

Journal of Construction Division, Vol. 94, No. CO1, pp 75-88, New York,

N.Y., USA, 1968.

[3] Gates, M., and Scarpa, A. "Optimum Size of Hauling Units", ASCE, Journal

of the Construction Division, Vol. 101, No. CO4, pp 853-860, New York,

N.Y., USA, 1975.

[4] Gates, M., and Scarpa, A. "Criteria for the Selection of Construction

Equipment", ASCE, Journal of the Construction Division, Vol. 106, No.

CO2, pp 207-219, New York, N.Y., USA, 1980.

[5] Karshenas, S. "Truck Capacity Selection for Earthmoving", ASCE, Journal of

the Construction Engineering and Management. Vol. 115, No. 2, pp 212-227,

New York, N.Y., USA, 1989

[6] Karamihas S. M. and Gillespie T. D., "Characterizing Trucks for Dynamic

Load Prediction", International Journal of Heavy Vehicle Systems, Vol. 1,

No. 1, pp 3-19, USA, 1993

[7] Havers, J.A., and Stubbs. F.W. "Handbook of Heavy Construction", 2nd

ed,

McGraw-Hill, Inc., New York, N.Y., USA, 1971.

[8] James Y. and Tom M., "Applicability Of Performance-Based Standards To

Truck Size and Weight Regulation in The United States", Road Transport

Technology, Proceedings of the Fourth International Symposium on Heavy

Vehicle Weights and Dimensions, Ann Arbor, 1995.

[9] Nagatani, T., "Bunching transition in a time headway model of a bus route",

131

Journals of the American Physical Society, Rev. E, vol. 63, no. 3, paper

036115, USA, 2001.

[10] Jack H. Willenbrock "Estimating Costs of Earthwork via Simulation", ASCE,

Journal of the Construction Division, Vol. 98, No. 1, pp 49-60, USA, 1972

[11] Halpin, D. W. "CYCLONE: Method for Modeling of Job Site Processes"

Journal of the Construction Division, ASCE, vol. 103, no. 3, pp 489-499,

USA, 1977

[12] Mayer, R.H. Jr., and Stark, R.M. "Earthmoving Logistics", ASCE, Journal of

Construction Division, Vol. 107, No. CO2, pp 297- 312, New York, N.Y .,

USA, 1981

[13] Luch J. F., and Halpin D.W "Analysis of Construction Operations Using

Microcomputers", ASCE, Journal of the Construction Division, Vol. 108, No.

CO1, pp 129-145, USA, 1981

[14] Easa, S.M. "Earthwork Allocations with Nonconstant Unit Costs", ASCE,

Journal of Construction Engineering and Management, Vol. 113, No. 1, pp

34-50, New York, N.Y., USA, 1987

[15] Essa, S. M. "Selection of Roadway Grades that Minimize

Earthwork Cost Using Linear Programing", ASCE, Journal of the

Construction Division, Vol. 22A, No. 2, pp 121-136, USA, 1988

[16] Alkass, S. & Harris, F. "Expert System for Earthmoving Equipment Selection

in Road Construction", ASCE, Journal of the Construction Division, Vol.

114, pp 426-440, USA, 1988

[17] Ioannou, P.G. "UM-CYCLONE Discrete Event Simulation System,

Reference Manual", Report UMCE-89-11, Dept. of Civil Engineering,

University of Michigan, Ann Arbor, MI., 1989

[18] Amirkhanian , S.N., and Baker, N.J. "Expert System for Equipment Selection

132

for Earth-Moving Operations", ASCE, Journal of Construction Engineering

and Management, Vol. 118, No. 2, pp 318-331, New York, N.Y., USA, 1992.

[19] Hanna, A. ―SELECTCRANE: An Expert System for Optimum Crane

Selection‖ Proceedings on the 1st Conference of Computing in Civil Eng., pp

958-963, USA, 1994

[20] AbouRizk, S.M., Shi, J., ―Automated Construction Simulation Optimization‖,

ASCE, Journal of Construction Engineering and Management, Vol. 120,

No. 2, pp 374-385, USA, 1994

[21] Rong-Yau Huang, Grigoriadis, A.M., Halpin, D.W. "Simulation of cable-

stayed bridges using DISCO", Simulation Conference Proceedings, Vol. 11,

No. 2, pp 1130-1136, USA, 1994

[22] Tommelein, I.D., Carr, R.I., and Odeh, A.M. "Assembly of Simulation

Networks using Designs, Plans, and Methods", ASCE, Journal of the

Construction Division, Vol. 120, No. 4, pp 796-815, USA, 1994

[23] Christian, J. &Xie, T.X. ―Improving Earthmoving Estimating by More

Realistic Knowledge‖ Canadian Journal of Civil Eng., Vol. 23, No.2, pp 250-

259, Canada, 1996

[24] J.C. Martinez "STROBOSCOPE: state and resources based simulation of

construction processes", PhD Dissertation, Department of Civil and

Environmental Engineering, The University of Michigan, Ann Arbor, MI.,

USA, 1996

[25] Sawhney, A., and AbouRizk, S. "HSM - Simulation-based Project Planning

Method for Construction Projects", ASCE, Journal of the Construction

Division, Vol. 121, No. 3, pp 297-303, USA, 1995

[26] Hajjar, D.; AbouRizk, S. "Development of an object oriented framework for

the simulation ofearth moving operations", Intelligent Information Systems,

133

Vol. 8, pp 326-330, USA, 1997

[27] McCabe, B., ―Belief Networks in Construction Simulation‖, Proceedings of

the 33nd conference on Winter simulation, pp1279-1286, USA, 1998.

[28] Hajjar, D.; AbouRizk, S. "Simphony: an environment for building special

purpose constructionsimulation tools", Simulation Conference Proceedings,

Vol. 2, pp 998-1006, USA, 1999

[29] Naoum, S. and Haidar, A. ―A hybrid knowledge base system and genetic

algorithms for equipment selection‖, Journal of Engineering Construction

and Architectural Management, DOI: 10.1046, pp 3-14, USA, 2000

[30] Kannan, G., Schmitz, L. and Larsen, C. ―An industry perspective on the role

of equipment based earthmoving simulation‖, In Proceedings of the 2000

Winter Simulation Conference, pp 1945-1952, USA, 2000

[31] Bruno, Ernesto and Giovanni Cordeiro ―A Stochastic Colored Petri Net

Model To Allocate Equipments For Earth Moving Operations‖, ITcon Vol.

13, Prata et al, pg. 490, USA, 2008

[32] Raj Kapur, Nashwan and Serafim Castro ―Automatic Generation Of Progress

Profiles For Earthwork Operations Using 4d Visualisation Model‖, ITcon

Vol. 13, Shah et al, pg. 506, USA, 2008

[33] Peurifoy, P.E./Schexnayder, P.E "Construction Planning, Equipment, and

Methods", 6th. Ed. McGraw-Hill, Inc., New York, N.Y., USA, 2002.

[34] Frank Harris "Modern Construction and Ground Engineering Equipment and

Methods", 2nd

ed. Longman Group, United Kingdom, 1994.

[35] Construction Safety Standards Manual, Department Of Labor & Economic

Growth, Michigan, USA, 1999

[36] FAO Co., ―Cost Control in Forest Harvesting and Road Construction‖,FAO

Forestry Paper, Food and Agriculture Organization of the United Nations,

134

Rome, 1992

[37] HeshamRakha, IvanaLucic, "Variable Power Vehicle Dynamics Model for

Estimating Maximum Truck Acceleration Levels", Journal of Transportation

Engineering , Vol. 128, No 5, pp. 412-419, USA, 2002

[38] IvanaLucic, "Truck Modeling Along Grade Section", M. Eng. thesis, Virginia

Polytechnic Institute and State University, Virginia, USA, 2001.

[39] Douglas D. Gransberg, "Optimizing Haul Unit Size and Number Based on

Loading Facility Characteristics", Journal of Construction Engineering and

Management, ASCE, Vol. 122, No 3, pp. 248-253, USA, 1996

AAPPPPEENNDDIICCEESS

136

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SSeelleeccttiinngg tthhee ooppttiimmuumm eeqquuaattiioonn ffoorr ttrruucckk ssppeeeedd ((TThhee EExxaammpplleess))

11)) EExxaammppllee 11

Given: Its 730 Ejector Articulated Truck (Figure A.1) [1]

1. Gross power = 242 KW = 325 hp

2. Net power = 237 KW = 317 hp

3. Net empty weight = 25,550 kg = 56,328 lb

4. Assume load weight = payload = 28,100 kg = 61,950 lb

5. Gross weight = 53,650 kg = 118,278 lb

6. Haul road type = not smooth roadway (dirt roadway) Asphalt

7. Haul material type = hard clay

8. The haul road from the borrow site to the dump is 5 km downhill grade of

1%

9. Neglect air drag resistance force

Required: Estimate the haul truck speed from site to the dump

Results from given data:

1. Grade resistance = -1%

2. Grade resistance = 0.0981 x GVW x grade (4.23)

3. Grade resistance = 0.0981 x 53,650 x -1 = -5263 N

4. Rolling resistance = 4% (Dirt roadway Table 4.6)

5. Rolling resistance = GVW x R / 100 (4.24)

Where: R = rolling resistance per 100 kg vehicle weight (table A.1)

6. Rolling resistance = 53,650 x 17 / 100 = 9120.5 N

7. Bucket fill factor = 0.8 (hard clay material)

8. Weight of loose material = 1480 kg/m3 (hard clay material)

137

Figure A.1 Caterpillar Performance Handbook, 2006 (Articulated Trucks)

Table A.1 Rolling Resistance In Newton Per100 Kilogram Of Gross Weight

Type of road Rolling Resistance In Newton Per

100 Kilogram Of Gross Weight

Good Asphalt 12 N

Fair Asphalt 17 N

Poor Asphalt 22 N

Good Macadam 15 N

Poor Macadam 37 N

Dirt smooth 25 N

Dirt sandy 37 N

138

Traditional method:

Using truck performance chart (Figure A.2)

Total resistance = grade resistance + rolling resistance = -1 + 4 = 3%

Haul truck speed = 53 Km/hr

Method 1:

Speed (km/hr) = (273.75 x Engine HP) / (GMW x Total resistance)

GMW = gross machine operating weight = 53,650 kg

Total resistance = 3%

Speed (km/hr) = (273.75 x 317) / (53650 x 0.03) = 53.91 Km/hr

Method 2:

2 39.8066 ( )1000

r r

MR C c V c (4.26)

Rr = Rolling resistance = 9120.5 N, Grade resistance = -5263 N = 9.8066 M i

Total resistance = 9120.5 – 5263 = 3857.5 N, i = grade magnitude = - 0.01

cr = rolling coefficient = 1.75 (for fair asphalt) Table A.2

c2, c3 = rolling resistance constant = 0.0438, 6.1 Table A.3

M = vehicle mass = 53650 kg

Speed = (Rt – (9.8066 Cr C3 M / 1000) – (9.8066 M i)) / (9.8066 Cr C2 M / 1000)

Speed = 86.84 Km/hr

139

Figure A.2 730 Ejector Articulated Trucks Performance chart

Table A.2 Highway surface coefficients [38]

140

Table A.3 Rolling resistance constants[38]

Method3:

3600t

PF

V (4.27)

Ft = Tractive force = 9.8066 Mta μ = 94241.43 N, η = transmission efficiency = 0.94

(Table A.2), P = Energy power = 237 kW, V = Truck speed (Km/hr)

Mta = Mass on tractive Rear axle = 19229 kg (from truck catalogue)

μ = Coefficient of friction = 0.5 (Table A.4)

Speed = V = 8.5 Km/hr

Table A.4 Transmission efficiency [39]

141

Method4:

375( )( )

( 20( ))H

F

hp ev

W RR S

(4.28)

VH = velocity of haul direction (mph)

Hp = Engine horsepower = 317 hp

e = engine efficiency = 1 at net power

RR = rolling resistance = 4% x 20 lb/ton = 80 lb/ton

Wf = weight fully loaded ( 1 long ton = 909.09 kg)

Wf = 53650 / 909.09 = 59 lton

S = slope of haul road = - 1%

Speed = VH = 54 Km/hr

142

22)) EExxaammppllee 22

Given: Its725 Articulated Truck (Figure A.1) [1]

1. Gross power = 230 KW = 309hp

2. Net power = 225 KW = 301hp

3. Net empty weight = 22,260 kg = 49,075lb

4. Assume load weight = payload = 23,590 kg = 52,007lb

5. Gross weight = 45,850 kg = 101,082lb

6. Haul road type = not smooth roadway (dirt roadway) Asphalt

7. Haul material type = hard clay

8. The haul road from the borrow site to the dump is 5 km downhill grade of

1%

9. Neglect air drag resistance force

Required: Estimate the haul truck speed from site to the dump

Results from given data:

1. Grade resistance = -1%

2. Grade resistance = 0.0981 x GVW x grade

3. Grade resistance = 0.0981 x 45,850 x -1 = - 4498 N

4. Rolling resistance = 4% (Dirt roadway Table 4.6)

5. Rolling resistance = GVW x R / 100

Where: R = rolling resistance per 100 kg vehicle weight (table A.1)

6. Rolling resistance = 45,850 x 17 / 100 = 7794.5 N

7. Bucket fill factor = 0.8 (hard clay material)

8. Weight of loose material = 1480 kg/m3 (hard clay material)

143

Traditional method:

Using truck performance chart (figure A.3)

Total resistance = grade resistance + rolling resistance = -1 + 4 = 3%

Haul truck speed = 56 Km/hr

Figure A.3 730 Ejector Articulated Trucks Performance chart

Method 1:

Speed (km/hr) = (273.75 x Engine HP) / (GMW x Total resistance)

GMW = gross machine operating weight = 45,850 kg

Total resistance = 3%

Speed (km/hr) = (273.75 x 301) / (45850 x 0.03) = 59.90 Km/hr

144

Method 2:

2 39.8066 ( )1000

r r

MR C c V c

Rr = Rolling resistance = 7794.5 N, Grade resistance = - 4498 N = 9.8066 M i, Total

resistance = 7794.5 – 4498 = 3296.5 N

i = grade magnitude = - 0.01

cr = rolling coefficient = 1.75 (for fair asphalt) table A.2

c2, c3 = rolling resistance constant = 0.0438, 6.1 table A.3

M = vehicle mass = 45850 kg

Speed = (Rt – (9.8066 Cr C3 M / 1000) – (9.8066 M i)) / (9.8066 Cr C2 M / 1000)

Speed = 86.86 Km/hr

Method 3:

3600t

PF

V

Ft = Tractive force = 9.8066 Mta μ = 74412.5 N, η = transmission efficiency = 0.94

(Table A.4), P = Energy power = 225 KW, V = Truck speed (Km/hr), Mta = Mass

on tractive Rear axle = 15176 kg (from truck catalogue), μ = Coefficient of friction

= 0.5 (Table A.2)

Speed = V = 10.23 Km/hr

Method 4:

375( )( )

( 20( ))H

F

hp ev

W RR S

145

VH = velocity of haul direction (mph), Hp = Engine horsepower = 301hp, e =

engine efficiency = 1 at net power, RR = rolling resistance = 4% x 20 lb/ton = 80

lb/ton, Wf = weight fully loaded (1 long ton = 909.09 kg), Wf = 45850 / 909.09 =

50.43lton, S = slope of haul road = - 1%

Speed = VH = 60.1 Km/hr

146

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SSeelleecctteedd pprroodduuccttiioonn eeqquuaattiioonnss vviissuuaall bbaassiicc..nneett ccooddeess

PublicFunction production_eq()

Dim B AsDouble = add_db.qt7.Text' truck heaped capacity

Dim C AsDouble = qt8.Text' heaped bucket capacity for excavator

Dim D AsDouble = getValueFromDB("mat", "bucket_fill_fac", "ID = "&ed1.Sv) / 100

Dim FF1F AsDouble = qt10.Text' excavator cycle time

Dim FF2F AsDouble = getValueFromDB("mat", "cycle_time", "ID = "& ed1.Sv)

Dim F AsDouble

Dim LF AsDouble = getValueFromDB("mat", "load_factor", "ID = "& ed1.Sv)

Dim allresult(8) AsDouble

Dim AProB AsDoubleDim durhou AsDoubleDim durday AsDouble

Dim quandur AsDouble = et1.Text' quantity of excavated material

Dim htoddur AsDouble = es1.Value' number of working hours per day

Dim durweek AsDouble = es2.Value' number of working days per week

If FF1F = 0 ThenF = FF2FElseF = FF1FEndIf

Dim I AsDouble = getValueFromDB("mat", "loose_wt_kg/m3", "ID = "& ed1.Sv)

Dim J AsDouble = add_db.qt3.Text' truck payload

Dim L AsDouble = add_db.qt2.Text' truck empty weight

Dim N1 AsDouble = fd1.SelectedValue' rolling resistance of the 1st road seg.

Dim N2 AsDouble = fd2.SelectedValue 'rolling resistance of the 2nd road seg.

Dim N3 AsDouble = fd3.SelectedValue' rolling resistance of the 3rd road seg.

Dim N4 AsDouble = fd4.SelectedValue' rolling resistance of the 4th road seg.

Dim N5 AsDouble = fd5.SelectedValue' rolling resistance of the 5th road seg.

Dim O1 AsDouble = fs1.Text' grade resistance of the 1st road seg.

Dim O2 AsDouble = fs2.Text' grade resistance of the 2nd road seg.

Dim O3 AsDouble = fs3.Text' grade resistance of the 3rd road seg.

Dim O4 AsDouble = fs4.Text' grade resistance of the 4th road seg.

Dim O5 AsDouble = fs5.Text' grade resistance of the 5th road seg.

Dim M AsDouble = add_db.qt5.Text' truck engine net power

Dim P1 AsDouble = ft1.Text' distance of the 1st road seg. From hauling site to dump site

Dim P2 AsDouble = ft2.Text' distance of the 2nd road seg. From hauling site to dump

Dim P3 AsDouble = ft3.Text' distance of the 3rd road seg. From hauling site to dump site

Dim P4 AsDouble = ft4.Text' distance of the 4th road seg. From hauling site to dump site

Dim P5 AsDouble = ft5.Text' distance of the 5th road seg. From hauling site to dump site

Dim Y AsDouble = ed2.SelectedValue' job effeciency factor

Dim Z AsDouble = ed3.SelectedValue' operator effeciency factor

Dim Spll AsDouble = add_db.qt6.Text' truck top speed at loaded

Dim Splg1 AsDouble = ft6.Text' legal speed limit of the 1st road seg.

Dim Splg2 AsDouble = ft7.Text' legal speed limit of the 2nd road seg.

Dim Splg3 AsDouble = ft8.Text' legal speed limit of the 3rd road seg.

Dim Splg4 AsDouble = ft9.Text' legal speed limit of the 4th road seg.

Dim Splg5 AsDouble = ft10.Text' legal speed limit of the 5th road seg.

Dim A1Test, A2Test, A3Test, WeightTest1, WeightTest2, A, A1, A2, EA1, EA2, GA1, GA2, GA1R,

GA2R, GA1F, GA2F, HA1, HA2, KA1, KA2, N1M, N2M, N3M, N4M, N5M, O1M, O2M, O3M, O4M, O5M,

upup, fdownA1R1, fdownA1R2, fdownA1R3, ….. (all remaining data)AsDouble

A = B / (C * D)

A1Test = Int(A)A2Test = Int(A) + 1A3Test = Int(A) - 1

WeightTest1 = A1Test * C * D * I

If WeightTest1 > J ThenA1 = A3TestElse= A1TestEndIf

EA1 = A1 * F / 60

GA1 = A1 * C * D

If GA1 > B ThenGA1R = BElseGA1R = GA1EndIf

HA1 = GA1R * I

GA1F = GA1R

WeightTest2 = A2Test * C * D * I

If WeightTest2 > J ThenA2 = A1ElseA2 = A2TestEndIf

EA2 = A2 * F / 60

GA2 = A2 * C * D

If GA2 > B ThenGA2R = BElse= GA2EndIf

HA2 = GA2R * I

GA2F = GA2RKA1 = HA1 + LKA2 = HA2 + LN1M = N1 * 20

N2M = N2 * 20N3M = N3 * 20N4M = N4 * 20N5M = N5 * 20

O1M = O1 * 20O2M = O2 * 20O3M = O3 * 20O4M = O4 * 20

O5M = O5 * 20upup = 375 * M

fdownA1R1 = (KA1 / 909.09) * (N1M + O1M)

fdownA1R2 = (KA1 / 909.09) * (N2M + O2M)

fdownA1R3 = (KA1 / 909.09) * (N3M + O3M)

147

fdownA1R4 = (KA1 / 909.09) * (N4M + O4M)

fdownA1R5 = (KA1 / 909.09) * (N5M + O5M)

fdownA2R1 = (KA2 / 909.09) * (N1M + O1M)

fdownA2R2 = (KA2 / 909.09) * (N2M + O2M)

fdownA2R3 = (KA2 / 909.09) * (N3M + O3M)

fdownA2R4 = (KA2 / 909.09) * (N4M + O4M)

fdownA2R5 = (KA2 / 909.09) * (N5M + O5M)

edownAR1 = (L / 909.09) * (N1M - O1M)

edownAR2 = (L / 909.09) * (N2M - O2M)

edownAR3 = (L / 909.09) * (N3M - O3M)

edownAR4 = (L / 909.09) * (N4M - O4M)

edownAR5 = (L / 909.09) * (N5M - O5M)

R1A1test = (upup / fdownA1R1) * 1.61










If R1A1test < 0 ThenR1A1test2 = SpllElseR1A1test2 = R1A1testEndIf










R1A1 = Math.Min(R1A1test2, Spll)










S1test = (upup / edownAR1) * 1.61





If S1test < 0 ThenS1test2 = Splg1ElseS1test2 = S1testEndIf





S1 = Math.Min(S1test2, Splg1)





T1A1 = ((P1 / 1000) * 60) / R1A1

T2A1 = ((P2 / 1000) * 60) / R2A1

T3A1 = ((P3 / 1000) * 60) / R3A1

T4A1 = ((P4 / 1000) * 60) / R4A1

T5A1 = ((P5 / 1000) * 60) / R5A1

T1A2 = ((P1 / 1000) * 60) / R1A2

T2A2 = ((P2 / 1000) * 60) / R2A2

T3A2 = ((P3 / 1000) * 60) / R3A2

T4A2 = ((P4 / 1000) * 60) / R4A2

T5A2 = ((P5 / 1000) * 60) / R5A2

If S1 = 0 ThenU1 = 0ElseU1 = P1 / (S1 * (1000 / 60)) EndIf

If S2 = 0 ThenU2 = 0ElseU2 = P2 / (S2 * (1000 / 60)) EndIf

…..

WA1 = EA1 + T1A1 + T2A1 + T3A1 + T4A1 + T5A1 + U1 + U2 + U3 + U4 + U5 + 2

WA2 = EA2 + T1A2 + T2A2 + T3A2 + T4A2 + T5A2 + U1 + U2 + U3 + U4 + U5 + 2

XA1 = WA1 / ((A1 * F) / 60)

XA2 = WA2 / ((A2 * F) / 60)

If XA1 < 1 ThenX1A1 = 1ElseX1A1 = Int(XA1)EndIf

If XA2 < 1 ThenX1A2 = 1ElseX1A2 = Int(XA2) EndIf

148

X2A1 = Int(XA1) + 1

X2A2 = Int(XA2) + 1

If WA1 = 0 ThenProdu1A1 = 0ElseProdu1A1 = (X1A1 * GA1F * 60 * Y * Z) / WA1EndIf

…….etc.

AProdu1 = Math.Max(Produ1A1, Produ2A1)

AProdu2 = Math.Max(Produ1A2, Produ2A2)

AProdu = Math.Max(AProdu1, AProdu2)

allresult(0) = AProdu

If AProdu = Produ1A1 Or AProdu = Produ2A1 ThenAbuck = A1ElseAbuck = A2EndIf

If AProdu = Produ1A1 ThenAtruck = X1A1ElseIf AProdu = Produ2A1 ThenAtruck = X2A1

ElseIf AProdu = Produ1A2 ThenAtruck = X1A2ElseAtruck = X2A2EndIf

If AProdu = Produ1A1 Or AProdu = Produ2A1 Then

AespA = S1

AProB = AProdu * LF

If er1.Checked = TrueThendurhou = quandur / AProduElsedurhou = quandur / AProBEndIf

If htoddur = 0 Thendurday = 0Elsedurday = durhou / htoddurEndIf

allresult(1) = Abuckallresult(2) = Atruckallresult(3) = AlspA

allresult(4) = AespAallresult(5) = AProBallresult(6) = durhouallresult(7) = durday

Return allresultEndFunction

PrivateSub ru_Click(ByVal sender As System.Object, ByVal e As System.EventArgs)

EndSub

Function getValueFromDB(ByVal tablename AsString, ByVal field AsString, ByVal condition

AsString)

conn.Open()

Dim DataAdapter1 AsNew OleDbDataAdapter("SELECT * FROM "& tablename, conn)

DataAdapter1.Fill(dataset4, tablename)

conn.Close()

Dim aaa() As DataRow = dataset4.Tables(tablename).Select(condition)

Return aaa(0)(field).ToString

EndFunction

PublicFunctionfinishduration()

Dim durweek AsDouble = es2.Value

Dim actualdays AsDouble

Dim finishdate(1) AsDate


Dim dattt AsDate = pc2.Value

allresult = production_eq()

If durweek = 0 Thenactualdays = 0Elseactualdays = (allresult(7) / durweek) * 7

EndIf

finishdate(0) = DateSerial((dattt.Year), (dattt.Month), (dattt.Day) + actualdays)

Return finishdate

EndFunction

149

AAppppeennddiixx CC

SSeelleecctteedd uunniitt ccoosstt eeqquuaattiioonnss vviissuuaall bbaassiicc..nneett ccooddeess

PublicFunction excavator_truck_cose()

Dim Ghp AsDouble = TextBox1.Text' excavator gross engine horsepower

Dim Exp AsDouble = xt1.Text' excavator purchase price

Dim Exs AsDouble = xt6.Text' excavator salvage price

Dim Exi AsDouble = xt2.Text / 100' excatator interest rate

Dim Exu AsDouble = xt7.Text / 100' excavator insurance rate

Dim Ext AsDouble = xt3.Text / 100' excavator taxes rate

Dim Exl AsDouble = xt8.Text' excavator operator cost

Dim Exh AsDouble = xt4.Text' excavator helper cost

Dim Exfl AsDouble = xt5.Text' cost of fuel per liter for excavator

Dim ExRental AsDouble = xt10.Text' excavator rental cost

Dim allresult_cost(9) AsDouble

Dim Exd, Exic, Exuc, Extc, Exf, Exr, Exlu, Exct, Exctm, Exctb AsDouble

Dim hd_dd AsDouble = es1.Value' number of working hours per day

Dim wd_dd AsDouble = es2.Value' number of working days per week


Dim Ghpt AsDouble = add_db.qt1.Text' truck engine gross power

Dim trp AsDouble = tt1.Text' truck purchase price

Dim trs AsDouble = tt7.Text' truck salvage price

Dim tri AsDouble = tt2.Text / 100' truck interest rate

Dim tru AsDouble = tt8.Text / 100' truck insurance rate

Dim trt AsDouble = tt3.Text / 100' truck taxes rate

Dim trl AsDouble = tt9.Text' truck operator cost

Dim trh AsDouble = tt4.Text' truck helper cost

Dim trfl AsDouble = tt5.Text' cost of fuel per liter for truck

Dim trti AsDouble = tt6.Text' truck tire cost

Dim trRental AsDouble = tt11.Text' truck rental cost

Dim trd, tric, truc, trtc, trf, trr, trlu, trct, trctm, trctb, trtit AsDouble

Dim Tcotex, Tcotexm, Tcotexb AsDouble

allresult = production_eq()

If tr1.Checked = TrueThen

If t5000.Checked = TrueThentrd = (trp - trs) / 25000

ElseIf t3000.Checked = TrueThentrd = (trp - trs) / 20000Else

trd = (trp - trs) / 15000EndIf

tric = (trp * 0.6 * tri) / (52 * wd_dd * hd_dd)

……etc

If tr3.Checked = TrueThentrf = Ghpt * 0.17 * 0.54 * trfl / 0.84Elsetrf = Ghpt * 0.21 * 0.54

* trfl / 0.72

EndIftrr = trdtrlu = 0.1 * trf

If t5000.Checked = TrueThentrtit = 1.2 * (trti / 5000)

ElseIf t3000.Checked = TrueThentrtit = 1.2 * (trti / 3000)Elsetrtit = 1.2 * (trti / 1500)

EndIf

trct = (allresult(2) * (trd + tric + truc + trtc + trf + trr + trlu + trl + trtit + 5)) +

(trh * tt10.Text)

Elsetrct = allresult(2) * trRentalEndIf

If xr1.Checked = TrueThen

If t5000.Checked = TrueThenExd = (Exp - Exs) / 12000ElseIf t3000.Checked = TrueThen

Exd = (Exp - Exs) / 10000ElseExd = (Exp - Exs) / 8000EndIf

Exic = (Exp * 0.6 * Exi) / (52 * wd_dd * hd_dd)

Exuc = (Exp * 0.6 * Exu) / (52 * wd_dd * hd_dd)

Extc = (Exp * 0.6 * Ext) / (52 * wd_dd * hd_dd)

If xr3.Checked = TrueThenExf = Ghp * 0.17 * 0.54 * Exfl / 0.84ElseExf = Ghp * 0.21 * 0.54 *

Exfl / 0.72EndIf

Exr = ExdExlu = 0.1 * Exf

Exct = Exd + Exic + Exuc + Extc + Exf + Exr + Exlu + Exl + (Exh * xt9.Text) + 5

Else

Exct = ExRental

EndIf

Exctm = Exct / allresult(0)

Exctb = Exct / allresult(5)

trctm = trct / allresult(0)

trctb = trct / allresult(5)

allresult_cost(0) = Exct

allresult_cost(1) = Exctm

allresult_cost(2) = Exctb

150

allresult_cost(3) = trct

allresult_cost(4) = trctm

allresult_cost(5) = trctb

Tcotex = Exct + trct

Tcotexm = Exctm + trctm

Tcotexb = Exctb + trctb

allresult_cost(6) = Tcotex

allresult_cost(7) = Tcotexm

allresult_cost(8) = Tcotexb

Return allresult_cost

EndFunction

151

AAppppeennddiixx DD

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From: Caterpillar. "Caterpillar Performance Handbook", ed. 36th.Caterpillar Tractor Company, Peoria,

Illinois, USA, 2006.

The digging cycle of the excavator is composed of four segments:Load Bucket,

Swing Loaded, Dump Bucket and Swing Empty. Total excavator cycle time is

dependent on machine size (small machines can cycle faster than large machines)

and job conditions. With excellent job conditions the excavator can cycle fast. As

job conditions become more severe (tougher digging, deeper trench, more obstacles,

etc.), the excavator slows down accordingly. As the soil gets harder to dig, it takes

longer to fill the bucket. As the trench gets deeper and the spoil pile larger, the

bucket has to travel farther and the upper structure has to swing farther on each

digging cycle.Spoil pile or truck location also affects cycle time. If a truck is located

on the floor of the excavation beside material being moved, 10 to 17 second cycles

are practical. The other extreme would be a truck or spoil pile located above the

excavator 180° from the excavation.In sewer construction work the operator may

not be able to work at full speed because he has to dig around existing utilities, load

the bucket inside a trench shield, or avoid people working in the area.

The Cycle Time Estimating Chart outlines the range of total cycle time that

can be expected as job conditions range from excellent to severe. Many variables

affect how fast the excavator is able to work. The chart defines the range of cycle

times frequently experienced with a machine and provides a guide to what is an

―easy‖ or a ―hard‖ job. The estimator can then evaluate the conditions of his job and

use the Cycle Time Estimating Chart to select the appropriate working range.

Apractical method of further calibrating the Cycle Time Estimating Chart is to

observe excavators working in the field and correlate measured cycle times to job

conditions, operator ability, etc.

152

The following table breaks down what experience has shown to be typical

Caterpillar excavator cycle times with

no obstruction in the right of way

above average job conditions

an operator of average ability and

60°-90° swing angle.

These times would decrease as job conditions or operator ability improved and

would get slower as conditions become less favorable.

153

154

AAppppeennddiixx EE

OOwwnniinngg aanndd ooppeerraattiinngg ccoosstt eessttiimmaattiinngg ffoorrmm

From: Caterpillar. "Caterpillar Performance Handbook", ed. 36th.Caterpillar Tractor Company, Peoria,

Illinois, USA, 2006.

155

156

AAppppeennddiixx FF

SSeelleecctteedd EExxcceell ccooddeess uusseedd iinn tthhee ssiimmuullaattiioonn

Beta distribution:

The Beta distribution can often be used to model random variables that vary between two

finite limits. For example, a beta distribution is quite useful for modeling proportions. By

ed density

having a domain on (0, 1). Increasing either parameter by itself moves the mean of the

distribution (to the right or left, respectively). Increasing both parameters together

decreases the variance and hence causes the distribution to be concentrated close to the

mean. By further taking a transformation such as Y = aX + b, one can get almost any

desired density on the interval (b,a+b).

To obtain a Beta distribution on some other interval (b, a+b), simply transform by Y = aX +

b. The mean and variance will change appropriately. For the general beta distribution on

[a,b], it is possible to calculate values of the CDF (cumulative density functions) using

EXCEL. The command line is “=BETADIST(x a,b)”. The parameters are as

above, and the value for x is the value at which we wish to evaluate the CDF. For nice

polynomial PDFs (probability density functions), the CDF can also be easily computed by

integration.

Plots of the PDF for several different parameterizations of the Beta distribution are shown

below.Note the variety of shapes that this distribution can take depending on these

parameters.

157

In EXCEL The BETAINV(p, alpha, beta, A, B) function is the inverse function for

BETADIST(x, alpha, beta, A, B). For any particular x, BETADIST(x, alpha, beta, A, B)

returns the probability that a Beta-distributed random variable (with the parameters alpha,

beta, A, and B) is less than or equal to x. In other words, BETADIST returns the

cumulative probability that is associated with x. If A and B are removed, they are assumed

to be 0 and 1, respectively. The BETAINV(p, alpha, beta, A, B) function returns the value

of x where BETADIST(x, alpha, beta, A, B) returns p. Therefore, BETAINV is evaluated by

158

a search process that returns the appropriate value of x by evaluating BETADIST for

various candidate values of x until it finds a value of x where BETADIST(x, alpha, beta, A,

B) is "acceptably close" to p. In this study case p is a random variable, A is a Minimum

value and B is a Maximum value

Normal distribution:

The shape resembles a bell symmetric around the mean (μ). The standard deviation (σ)

determines the concentration of variates around μ : the smaller σ the variates are more

concentrated. σ must be positive.

Probability density function:

The mean and standard deviation are µ and σ. The values from the Normal distribution

are generated by the following formulas:

=norminv(RAND(),mean, standard deviation)

This formulas Returns the inverse of the normal cumulative distribution for the specified

mean and standard deviation.

NORMINV(probability,mean,standard_dev)

Probability: is a probability corresponding to the normal distribution.

Mean: is the arithmetic mean of the distribution.

Standard_dev: is the standard deviation of the distribution.

Given a value for probability, NORMINV seeks that value x such that NORMDIST(x,

mean, standard_dev, TRUE) = probability. Thus, precision of NORMINV depends on

159

precision of NORMDIST. NORMINV uses an iterative search technique. If the search has

not converged after 100 iterations, the function returns the #N/A error value.

Crystal Ball MACRO Codes

Simulation running:

CB.RunPrefsNDcbRunMaxTrials, 100000

CB.RunPrefsNDcbRunStopOnError, True

CB.RunPrefsNDcbRunSameRandoms, False

CB.RunPrefsNDcbRunSamplingMethod, cbSamMonteCarlo

CB.RunPrefsNDcbRunCorrelationsOff, False

CB.RunPrefsNDcbRunMode, cbRunExtremeSpeed

CB.RunPrefsNDcbRunPrecisionControl, True

CB.RunPrefsNDcbRunPrecisionConfidence, 95

CB.RunPrefsNDcbRunReversePercentiles, False

CB.RunPrefsNDcbRunFormatPercentiles, False

CB.RunPrefsNDcbRunSaveAssumptionValues, True

CB.RunPrefsNDcbRunLeaveOpenOnReset, True

CB.RunPrefsNDcbRunUserMacros, True

CB.RunPrefsNDcbRunCapMetrics, False

CB.Simulation x,, True, True, True

Reports exporting:

CB.CheckData

CB.CreateRptNDcbRptSection, True, cbRptSectForecasts

CB.CreateRptNDcbRptDefinedType, cbRptCustom

CB.CreateRptNDcbRptTrendCharts, False

CB.CreateRptNDcbRptSensitivityCharts, False

CB.CreateRptNDcbRptOverlayCharts, False

CB.CreateRptNDcbRptSummary, cbRptSummaryTitle

CB.CreateRptNDcbRptSummary, cbRptSummaryDate

CB.CreateRptNDcbRptSummary, cbRptRunPreferences

CB.CreateRptNDcbRptSummary, cbRptRunStatistics

CB.CreateRptNDcbRptChooseFore, cbChfAll

CB.CreateRptNDcbRptForeSummaries, True

160

CB.CreateRptNDcbRptForeStatistics, True

CB.CreateRptNDcbRptForeCharts, True, 100

CB.CreateRptNDcbRptForePercentiles, True, cbPctDeciles

CB.CreateRptNDcbRptChooseAssum, cbChaClearList

CB.CreateRptNDcbRptChooseAssum, cbChaChosen

CB.CreateRptNDcbRptChartType, cbChtColored

CB.CreateRptNDcbRptSheetName, Results Report (20000 trials)

CB.CreateRptNDcbRptIncludesCellLocs, True

CB.CreateRptNDcbRptOK

CB.CheckData

CB.ExtractDataNDcbExtChooseFore, cbChfAll

CB.ExtractDataNDcbExtChooseAsm, cbChaClearList

CB.ExtractDataNDcbExtDataType, cbDatPercentiles

CB.ExtractDataNDcbExtPercentiles, cbPctDeciles

CB.ExtractDataNDcbExtDataType, cbDatFrequencies

CB.ExtractDataNDcbExtChartBins, 100

CB.ExtractDataNDcbExtExistingSheet, True

CB.ExtractDataNDcbExtIncludeLabels, True

CB.ExtractDataNDcbExtAutoFormat, True

CB.ExtractDataNDcbExtSheetName, Results Charts Bins

CB.ExtractDataNDcbExtOK

Some important definitions:

Mean: The mean of a set of values is found by adding the values and dividing their sum

by the number of values. The term "average" usually refers to the mean. For example, 5.2

is the mean or average of 1, 3, 6, 7, and 9.

Standard deviation: The standard deviation is the square root of the variance for a

distribution. Like the variance, it is a measure of dispersion about the mean and is useful

for describing the "average" deviation.For example, you can calculate the standard

deviation of the values 1, 3, 6, 7, and 9 by finding the square root of the variance that is

calculated in the variance example below.

161

The standard deviation, denoted as s, is calculated from the variance as follows: where

the variance is a measure of the dispersion, or spread, of a set of values about the mean.

When values are close to the mean, the variance is small. When values are widely

scattered about the mean, the variance is larger. To calculate the variance of a set of

values:Find the mean or average, For each value, calculate the difference between the

value and the mean, Square these differences and Divide by n-1, where n is the number

of differences.For example, suppose your values are 1, 3, 6, 7, and 9. The mean is 5.2.

The variance, denoted by s2, is calculated as follows:

Median: The median is the number in the middle of a set of numbers.

Mode: Returns the most frequently occurring, or repetitive, value in an array or range of

data.

Kurtosis: Kurtosis characterizes the relative peakedness or flatness of a distribution

compared with the normal distribution. Positive kurtosis indicates a relatively peaked

distribution. Negative kurtosis indicates a relatively flat distribution.

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